DESC:Field of the Invention
The present invention relates to intelligent surveillance and monitoring systems for power distribution infrastructure, and more particularly to an adaptive intelligent surveillance retrofit system for transformers and field infrastructure assets using operational-event intelligence, contextual visual verification, adaptive surveillance escalation, temporal threat persistence analysis, and communication-aware evidence management for real-time threat validation and visual response orchestration.

Background of the Invention
Electrical transformers and field infrastructure assets deployed in power distribution networks are frequently installed in remote, semi-urban, and geographically distributed environments where such assets remain exposed to various operational and physical security risks. Such risks may include unauthorized access, enclosure tampering, vandalism, copper theft, oil leakage, infrastructure damage, and other abnormal conditions capable of disrupting power distribution operations and compromising infrastructure reliability.
Intelligent transformer monitoring systems, including Smart Transformer Monitoring Units (STMUs), have been developed for monitoring operational and security-related conditions associated with transformer assets. Such systems generally utilize sensor-based telemetry, vibration sensing, tamper detection mechanisms, thermal monitoring modules, electrical parameter monitoring, and communication interfaces for detecting abnormal operational conditions including overheating, unauthorized movement, enclosure tampering, theft-risk events, and infrastructure anomalies. Upon detection of such conditions, existing monitoring systems typically generate alerts or notifications for further investigation and response by utility operators. However, such systems generally generate alerts without providing contextual visual verification capable of accurately determining the actual physical condition associated with detected anomalies.
In parallel, conventional surveillance systems including closed-circuit television (CCTV) systems and event-triggered camera systems are commonly utilized for visual monitoring of utility infrastructure environments. Certain surveillance systems may activate image capture operations in response to motion detection, intrusion detection, or external trigger signals generated by monitoring devices. However, such surveillance systems generally operate independently from transformer operational intelligence and are incapable of contextually verifying whether detected human activity, environmental interaction, or physical movement actually corresponds to a genuine transformer threat condition. Consequently, existing systems frequently generate excessive false visual alerts, unnecessary escalation operations, and inefficient surveillance activities associated with non-threatening or operationally irrelevant events.
Further, existing event-triggered surveillance systems typically utilize fixed threshold-based activation mechanisms and react uniformly to detected events without dynamically evaluating contextual threat severity, operational conditions, or visual relevance associated with detected transformer events. As a result, conventional surveillance systems generally perform identical or static image capture operations irrespective of threat persistence, event progression, or contextual operational conditions, thereby causing excessive image generation, inefficient bandwidth utilization, unnecessary storage consumption, and poor surveillance prioritization.
Additionally, existing surveillance architectures typically process detected events independently and lack temporal persistence analysis mechanisms capable of identifying recurring, evolving, or progressively escalating transformer threat conditions over time. Consequently, repeated suspicious activities, progressive tampering attempts, or persistent threat behaviors may not be intelligently differentiated from transient disturbances, maintenance activity, environmental conditions, or isolated non-threatening interactions occurring near transformer infrastructure.
Moreover, remote transformer and field infrastructure deployments frequently operate under resource-constrained conditions including unstable communication networks, intermittent LTE connectivity, limited bandwidth availability, battery constraints, and restricted power availability. However, conventional surveillance systems generally lack adaptive evidence management mechanisms capable of dynamically modifying image transmission behavior, storage operations, communication prioritization, or surveillance intensity according to communication quality conditions and deployment resource constraints. As a result, existing systems are technically unsuitable for large-scale geographically distributed utility infrastructure deployments due to excessive power consumption, continuous communication dependency, inefficient storage utilization, and unreliable visual threat verification capability.
Accordingly, there exists a need for an adaptive intelligent surveillance architecture capable of performing contextual visual threat verification and dynamically orchestrating surveillance operations according to transformer operational intelligence, contextual threat relevance, temporal threat persistence, communication quality conditions, and deployment resource constraints associated with transformers and field infrastructure assets.

Objective of the Invention
The principal objective of the present invention is to provide an adaptive intelligent surveillance retrofit system for transformers and field infrastructure assets capable of performing contextual visual threat verification and intelligent orchestration of surveillance operations in remote and distributed deployment environments.
Another objective of the present invention is to provide a multi-stage threat verification architecture configured to perform primary operational anomaly detection using a Smart Transformer Monitoring Unit (STMU) and secondary contextual visual verification using an intelligent surveillance subsystem for validating genuine transformer threat conditions.
Another objective of the present invention is to provide a contextual threat relevance evaluation mechanism capable of intelligently differentiating non-threatening activity, environmental disturbances, maintenance-related interactions, and operationally irrelevant events from genuine transformer threat behavior associated with transformers and field infrastructure assets.
Another objective of the present invention is to provide a threat-confidence-driven adaptive surveillance escalation mechanism configured to dynamically modify image capture operations, surveillance intensity, monitoring persistence, transmission priority, and visual response behavior according to contextual threat severity conditions.
Another objective of the present invention is to provide a temporal threat persistence analysis mechanism capable of identifying recurring, evolving, or progressively escalating transformer threat conditions through temporal correlation of operational anomalies and contextual visual activity associated with transformer infrastructure.
Another objective of the present invention is to provide a communication-aware and resource-aware evidence management mechanism configured to dynamically adapt image transmission operations, temporary evidence storage operations, alert communication behavior, and surveillance resource utilization according to communication quality conditions, network availability, and deployment resource constraints associated with remote transformer and field infrastructure environments.

Summary of the Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
The present invention provides an adaptive intelligent surveillance retrofit system and method for transformers and field infrastructure assets configured to perform contextual visual threat verification, adaptive surveillance orchestration, and communication-aware evidence management in remote and distributed deployment environments. The invention integrates operational-event intelligence, contextual visual monitoring, temporal threat analysis, adaptive surveillance escalation, and resource-aware communication control through a coordinated monitoring and surveillance architecture configured to support reliable threat verification, optimized surveillance operation, and scalable deployment across geographically distributed utility infrastructure environments. The system includes a monitoring subsystem, a surveillance subsystem, a communication subsystem, a storage subsystem, and a processing subsystem configured to collectively monitor operational and security-related conditions associated with transformers and field infrastructure assets. The monitoring subsystem monitors electrical parameters, vibration conditions, tamper-related conditions, thermal conditions, enclosure conditions, positional conditions, and infrastructure security conditions associated with transformer infrastructure assets and generates a primary threat indication corresponding to detected abnormal operational conditions or suspicious security-related events.
In another aspect, the surveillance subsystem is communicatively coupled with the monitoring subsystem and configured to perform contextual visual verification in response to the generated primary threat indication. The surveillance subsystem captures contextual visual information associated with an environment surrounding the transformer or the field infrastructure asset and performs secondary contextual verification by evaluating the contextual visual information in association with the primary threat indication to determine whether detected activity corresponds to a genuine transformer threat condition. The processing subsystem further performs contextual threat relevance evaluation capable of differentiating non-threatening human activity, maintenance-related interactions, environmental disturbances, or operationally irrelevant events from genuine transformer threat behavior associated with transformers and field infrastructure assets. The processing subsystem correlates operational-event intelligence, contextual visual information, tamper-related conditions, vibration-related conditions, enclosure interaction conditions, positional conditions, and temporal event characteristics to generate a threat confidence level corresponding to detected transformer threat conditions.
In another aspect, the processing subsystem performs temporal threat persistence analysis configured to evaluate repeated suspicious activity, recurring operational anomalies, progressive tampering conditions, prolonged transformer interaction behavior, or evolving threat activity occurring over a predefined time duration. The processing subsystem dynamically determines a surveillance escalation mode according to the generated threat confidence level, contextual threat relevance, temporal threat persistence information, operational conditions, and deployment resource conditions associated with the transformer or the field infrastructure asset. The surveillance escalation mode may include one or more of a snapshot capture mode, burst image capture mode, continuous monitoring mode, emergency surveillance transmission mode, adaptive reporting mode, low-power surveillance mode, or prioritized evidence transmission mode. The communication subsystem selectively performs adaptive evidence management according to communication quality conditions, network availability conditions, threat criticality conditions, and deployment resource constraints associated with remote transformer infrastructure deployments, including image transmission prioritization, adaptive image compression, temporary local evidence storage, delayed synchronization operations, text-based alert communication, or prioritized evidence transmission. Through the combination of the above features, the present invention improves contextual threat verification accuracy, reduces false visual alerts, reduces redundant image generation, optimizes bandwidth utilization, reduces power consumption, improves communication efficiency, and enhances operational reliability associated with transformers and field infrastructure assets deployed in geographically distributed and resource-constrained utility environments.

Brief description of the drawings
The figures described below depict various aspects of the system and methods disclosed herein. It should be understood that each figure depicts an embodiment of a particular aspect of the disclosed system and methods, and that each of the figures is intended to accord with a possible embodiment thereof. Further, wherever possible, the following description refers to the reference numerals included in the following figures, in which features depicted in multiple figures are designated with consistent reference numerals.
Figure 1 illustrates an example architecture (100) of an adaptive intelligent surveillance system for transformers and field infrastructure assets, according to one embodiment of the present invention.

Figure 2 illustrates an example internal architecture (200) of an adaptive intelligent surveillance subsystem configured for contextual verification, threat confidence generation, temporal persistence analysis, adaptive surveillance escalation, and evidence management, according to one embodiment of the present invention.
Figure 3 illustrates an example adaptive threat verification and surveillance orchestration workflow (300) associated with transformers and field infrastructure assets, according to one embodiment of the present invention.
Figure 4 illustrates an example adaptive surveillance escalation workflow (400) for dynamically modifying surveillance operations according to threat severity conditions associated with transformers and field infrastructure assets, according to one embodiment of the present invention.
Figure 5 illustrates an example communication-aware adaptive evidence management workflow (500) for selectively performing evidence transmission, temporary storage, and synchronization operations according to communication quality conditions associated with transformers and field infrastructure assets, according to one embodiment of the present invention.
Persons skilled in the art will appreciate that elements in the figures are illustrated for simplicity and clarity and may have not been drawn to scale. For example, the dimensions of some of the elements in the figure may be exaggerated relative to other elements to help to improve understanding of various exemplary embodiments of the present disclosure.
Throughout the drawings, it should be noted that like reference numbers are used to depict the same or similar elements, features, and structures.

Detailed Description of the Invention
The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of exemplary embodiments of the invention as defined by the claims and their equivalents. It includes various specific details to assist in that understanding but these are to be regarded as merely exemplary.
Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used by the inventor to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustration purpose only and not for the purpose of limiting the invention as defined by the appended claims and their equivalents.
It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a component surface” includes reference to one or more of such surfaces.
By the term “substantially” it is meant that the recited characteristic, parameter, or value need not be achieved exactly, but that deviations or variations, including for example, tolerances, measurement error, measurement accuracy limitations and other factors known to those of skill in the art, may occur in amounts that do not preclude the effect the characteristic is intended to provide.
Figures discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way that would limit the scope of the disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged system. The terms used to describe various embodiments are exemplary. It should be understood that these are provided to merely aid the understanding of the description, and that their use and definitions, in no way limit the scope of the invention. Terms first, second, and the like are used to differentiate between objects having the same terminology and are in no way intended to represent a chronological order, unless where explicitly stated otherwise. A set is defined as a non-empty set including at least one element.
Figure 1 illustrates an example architecture (100) of an adaptive intelligent surveillance system configured for transformers and field infrastructure assets, according to one embodiment of the present invention. The system architecture (100) includes a monitoring subsystem (102), an adaptive intelligent surveillance subsystem (104), a communication subsystem (106), a storage subsystem (108), and a remote monitoring platform (110) communicatively associated with one another for performing adaptive surveillance orchestration, contextual threat verification, and communication-aware evidence management associated with transformers and field infrastructure assets.
In an aspect, the monitoring subsystem (102) is configured to monitor one or more operational conditions and security-related conditions associated with a transformer or a field infrastructure asset. The monitoring subsystem (102) may include one or more monitoring devices, sensing devices, or intelligent monitoring units configured to monitor electrical conditions, vibration conditions, tamper-related conditions, thermal conditions, movement-related conditions, positional conditions, enclosure interaction conditions, or infrastructure security conditions associated with the transformer or the field infrastructure asset. Upon detection of an abnormal operational condition or suspicious security-related event, the monitoring subsystem (102) generates a primary threat indication associated with the transformer or the field infrastructure asset.
In another aspect, the adaptive intelligent surveillance subsystem (104) is communicatively coupled with the monitoring subsystem (102) and configured to perform contextual visual verification in response to the generated primary threat indication. The adaptive intelligent surveillance subsystem (104) captures contextual visual information associated with an environment surrounding the transformer or the field infrastructure asset and performs secondary contextual threat verification using the contextual visual information and the primary threat indication. The adaptive intelligent surveillance subsystem (104) is further configured to determine whether detected activity corresponds to genuine transformer threat activity or non-threatening activity associated with the transformer or the field infrastructure asset.
In another aspect, the adaptive intelligent surveillance subsystem (104) includes a contextual verification module configured to analyze contextual visual information associated with detected operational events. The adaptive intelligent surveillance subsystem (104) further includes a threat confidence generation module configured to generate a threat confidence level based on correlated evaluation of the primary threat indication, contextual visual information, tamper-related conditions, vibration-related conditions, movement-related conditions, enclosure interaction conditions, or temporal event characteristics associated with the transformer or the field infrastructure asset. In an embodiment, the threat confidence level may be dynamically determined using weighted priority values assigned to multiple operational-event conditions and contextual visual conditions associated with the transformer or the field infrastructure asset.
In another aspect, the adaptive intelligent surveillance subsystem (104) further includes a temporal persistence analysis module configured to evaluate recurring suspicious activity, repeated operational anomalies, progressive tampering conditions, or prolonged transformer interaction behavior associated with the transformer or the field infrastructure asset over a predefined time duration. Based on the generated threat confidence level and temporal threat persistence analysis, the adaptive intelligent surveillance subsystem (104) dynamically determines a surveillance escalation mode associated with the transformer or the field infrastructure asset.
In another aspect, the adaptive intelligent surveillance subsystem (104) performs adaptive surveillance escalation configured to dynamically modify surveillance operations according to determined contextual threat severity conditions associated with the transformer or the field infrastructure asset. The surveillance escalation mode may include one or more of a snapshot capture mode, burst image capture mode, continuous monitoring mode, emergency surveillance transmission mode, adaptive reporting mode, or prioritized evidence transmission mode.
In another aspect, the communication subsystem (106) is configured to perform adaptive evidence management associated with the transformer or the field infrastructure asset. The communication subsystem (106) selectively performs image transmission operations, image compression operations, temporary local evidence storage operations, delayed synchronization operations, alert communication operations, or prioritized evidence transmission operations according to communication quality conditions, contextual threat severity conditions, or deployment resource conditions associated with the transformer or the field infrastructure asset.
In another aspect, the storage subsystem (108) is configured to store contextual visual information, operational-event history, threat confidence information, surveillance escalation information, communication condition information, temporal threat persistence information, or evidence information associated with the transformer or the field infrastructure asset. The storage subsystem (108) further supports temporary local evidence buffering and delayed synchronization operations during reduced communication quality conditions or communication interruption conditions.
In another aspect, the remote monitoring platform (110) is configured to receive monitoring information, contextual visual evidence, alert information, surveillance escalation information, or threat-related information associated with transformers and field infrastructure assets for remote infrastructure monitoring, event analysis, threat visualization, and protection operations.
In an example embodiment, when the monitoring subsystem (102) detects abnormal vibration conditions or tamper-related conditions associated with a transformer, the monitoring subsystem (102) generates a primary threat indication and activates the adaptive intelligent surveillance subsystem (104). The adaptive intelligent surveillance subsystem (104) captures contextual visual information and performs contextual threat verification to determine whether detected human activity corresponds to maintenance-related activity or genuine transformer threat activity. Based on generated threat confidence information and temporal threat persistence analysis, the adaptive intelligent surveillance subsystem (104) dynamically determines an appropriate surveillance escalation mode and selectively performs evidence transmission, adaptive monitoring, or emergency alert communication operations through the communication subsystem (106).
Through coordinated interaction between the monitoring subsystem (102), adaptive intelligent surveillance subsystem (104), communication subsystem (106), storage subsystem (108), and remote monitoring platform (110), the system architecture (100) enables contextual threat verification, adaptive surveillance orchestration, communication-aware evidence management, reduced false visual alerts, optimized bandwidth utilization, adaptive deployment operation, improved evidence management, and enhanced operational reliability associated with transformers and field infrastructure assets deployed in geographically distributed and resource-constrained environments.
Figure 2 illustrates an example internal architecture (200) of an adaptive intelligent surveillance subsystem (104) configured for contextual visual verification, threat confidence generation, temporal threat persistence analysis, adaptive surveillance escalation, and adaptive evidence management associated with transformers and field infrastructure assets, according to one embodiment of the present invention.
In an aspect, the adaptive intelligent surveillance subsystem (104) includes a contextual visual acquisition module (202), a contextual verification module (204), a threat confidence generation module (206), a temporal persistence analysis module (208), an adaptive surveillance escalation module (210), a decision engine module (212), and an evidence management module (214) communicatively associated with one another for performing adaptive surveillance orchestration associated with transformers and field infrastructure assets.
In another aspect, the contextual visual acquisition module (202) is configured to capture contextual visual information associated with an environment surrounding a transformer or a field infrastructure asset in response to a primary threat indication generated by a monitoring subsystem. The contextual visual acquisition module (202) may include one or more image capture devices, surveillance cameras, low-power visual monitoring devices, or adaptive image acquisition devices configured to selectively capture contextual visual information according to contextual threat severity conditions associated with the transformer or the field infrastructure asset.
In another aspect, the contextual verification module (204) is configured to perform secondary contextual threat verification using the contextual visual information captured by the contextual visual acquisition module (202). The contextual verification module (204) evaluates contextual visual information in association with operational-event intelligence received from the monitoring subsystem to determine whether detected activity corresponds to genuine transformer threat activity or non-threatening activity associated with the transformer or the field infrastructure asset. In an embodiment, the contextual verification module (204) differentiates maintenance-related interaction, environmental disturbance, incidental human presence, or operationally irrelevant movement from suspicious transformer interaction behavior associated with the transformer or the field infrastructure asset.
In another aspect, the threat confidence generation module (206) is configured to generate a threat confidence level based on correlated evaluation of contextual visual information and operational-event intelligence associated with the transformer or the field infrastructure asset. The threat confidence generation module (206) may evaluate vibration-related conditions, tamper-related conditions, movement-related conditions, positional conditions, enclosure interaction conditions, temporal event characteristics, or contextual visual characteristics associated with the transformer or the field infrastructure asset.
In an embodiment, the threat confidence generation module (206) dynamically assigns weighted priority values to multiple operational-event conditions and contextual visual conditions to determine contextual threat severity associated with the transformer or the field infrastructure asset. In an example implementation, the threat confidence level (TC) may be determined using:
TC=?(Wn×En)
where:
TC represents the generated threat confidence level,
Wn represents weighted priority values assigned to detected event conditions, and
En represents detected operational-event conditions or contextual visual conditions associated with the transformer or the field infrastructure asset.
In an example embodiment, generated threat confidence levels may be represented using normalized confidence ranges between 0 and 100, wherein confidence values between 0–30 may correspond to non-threatening operational conditions, confidence values between 31–60 may correspond to moderate suspicious activity conditions, confidence values between 61–85 may correspond to elevated suspicious activity conditions, and confidence values above 85 may correspond to critical threat conditions associated with the transformer or the field infrastructure asset. In an embodiment, weighted priority values (Wn) assigned to operational-event intelligence and contextual visual information may range between 0.1 and 1.0 according to contextual threat relevance associated with the transformer or the field infrastructure asset.
In another embodiment, higher weighted priority values may be assigned to tamper-related conditions, enclosure interaction conditions, repeated suspicious activity, or abnormal transformer interaction behavior, whereas lower weighted priority values may be assigned to incidental environmental activity or non-threatening movement conditions.
In another aspect, the temporal persistence analysis module (208) is configured to evaluate recurring suspicious activity, repeated operational anomalies, progressive tampering conditions, or prolonged transformer interaction behavior occurring over a predefined time duration associated with the transformer or the field infrastructure asset. The temporal persistence analysis module (208) enables identification of recurring or progressively evolving transformer threat conditions that may not be identifiable through isolated event analysis.
In another aspect, the evidence management module (214) is configured to perform adaptive evidence management associated with transformers and field infrastructure assets. The evidence management module (214) selectively performs image transmission operations, image compression operations, temporary local evidence storage operations, delayed synchronization operations, or prioritized evidence transmission operations according to contextual threat severity conditions and communication quality conditions associated with the transformer or the field infrastructure asset.
In another aspect, the decision engine module (212) is configured to dynamically determine surveillance response operations based on generated threat confidence information, temporal threat persistence analysis, communication quality conditions, and deployment resource conditions associated with the transformer or the field infrastructure asset. The decision engine module (212) coordinates adaptive surveillance orchestration between the contextual verification module (204), threat confidence generation module (206), temporal persistence analysis module (208), adaptive surveillance escalation module (210), and evidence management module (214).
The decision engine module (212) may further dynamically coordinate surveillance escalation operations and communication-aware evidence management according to contextual threat severity conditions associated with the transformer or the field infrastructure asset.
In another aspect, the adaptive surveillance escalation module (210) is configured to dynamically modify surveillance operations according to generated contextual threat severity conditions associated with the transformer or the field infrastructure asset. The adaptive surveillance escalation module (210) selectively performs one or more of snapshot capture operations, burst image capture operations, continuous monitoring operations, emergency surveillance transmission operations, adaptive reporting operations, or prioritized evidence transmission operations according to generated threat confidence information and temporal persistence analysis associated with the transformer or the field infrastructure asset.
In an example embodiment, when the contextual visual acquisition module (202) captures visual information associated with detected human activity near a transformer, the contextual verification module (204) evaluates whether the detected activity corresponds to maintenance-related interaction or suspicious transformer interaction behavior. The threat confidence generation module (206) correlates contextual visual information with operational-event intelligence including vibration conditions, tamper-related conditions, or enclosure interaction conditions to generate a contextual threat confidence level. The temporal persistence analysis module (208) evaluates whether suspicious activity persists or recurs over time. Based on the generated threat confidence information and temporal persistence analysis, the decision engine module (212) activates the adaptive surveillance escalation module (210) to selectively perform snapshot capture operations, burst image capture operations, continuous monitoring operations, or emergency surveillance transmission operations. Simultaneously, the evidence management module (214) selectively performs adaptive evidence transmission, temporary local evidence storage, image compression operations, or delayed synchronization operations according to communication quality conditions associated with the transformer or the field infrastructure asset.
Through coordinated interaction between the contextual visual acquisition module (202), contextual verification module (204), threat confidence generation module (206), temporal persistence analysis module (208), adaptive surveillance escalation module (210), decision engine module (212), and evidence management module (214), the adaptive intelligent surveillance subsystem (104) enables contextual threat verification, adaptive surveillance orchestration, reduced false visual alerts, optimized bandwidth utilization, adaptive communication-aware evidence management, and improved operational reliability associated with transformers and field infrastructure assets deployed in geographically distributed and resource-constrained environments.
Figure 3 illustrates an example adaptive threat verification and surveillance orchestration workflow (300) associated with transformers and field infrastructure assets, according to one embodiment of the present invention. The workflow (300) enables coordinated monitoring, contextual threat verification, adaptive surveillance escalation, adaptive image management, and communication-aware evidence management associated with transformers and field infrastructure assets deployed in geographically distributed and resource-constrained environments.
In one embodiment, the workflow (300) implements a method for adaptive intelligent surveillance of transformers and field infrastructure assets. The method includes monitoring, by a monitoring subsystem, one or more operational conditions and security-related conditions associated with a transformer or a field infrastructure asset. The method further includes detecting, by the monitoring subsystem, an abnormal operational condition or a suspicious security-related event associated with the transformer or the field infrastructure asset and generating a primary threat indication corresponding to the detected abnormal operational condition or suspicious security-related event. In response to the generated primary threat indication, an adaptive intelligent surveillance subsystem communicatively coupled with the monitoring subsystem activates a contextual visual verification operation and captures contextual visual information associated with an environment surrounding the transformer or the field infrastructure asset. The adaptive intelligent surveillance subsystem performs secondary contextual threat verification using the contextual visual information and the primary threat indication to determine whether detected activity corresponds to genuine transformer threat activity or non-threatening activity associated with the transformer or the field infrastructure asset.
The adaptive intelligent surveillance subsystem further generates a threat confidence level based on correlated evaluation of the primary threat indication and the contextual visual information, wherein generating the threat confidence level includes correlating operational-event intelligence, contextual visual information, tamper-related conditions, vibration-related conditions, movement-related conditions, enclosure interaction conditions, or temporal event characteristics associated with the transformer or the field infrastructure asset. In an embodiment, generating the threat confidence level further includes assigning weighted priority values to the operational-event intelligence and the contextual visual information for dynamically determining contextual threat severity associated with the transformer or the field infrastructure asset. The method further includes performing temporal threat persistence analysis based on recurring suspicious activity, repeated operational anomalies, progressive tampering conditions, or prolonged transformer interaction behavior associated with the transformer or the field infrastructure asset. The adaptive intelligent surveillance subsystem determines a surveillance escalation mode according to the generated threat confidence level and the temporal threat persistence analysis, wherein determining the surveillance escalation mode includes dynamically selecting at least one of a snapshot capture mode, burst image capture mode, continuous monitoring mode, emergency surveillance transmission mode, adaptive reporting mode, or prioritized evidence transmission mode according to the generated threat confidence level and the temporal threat persistence analysis.
The method further includes performing adaptive evidence management according to the determined surveillance escalation mode and one or more communication quality conditions associated with the transformer or the field infrastructure asset, wherein performing the adaptive evidence management includes selectively performing image transmission operations, image compression operations, temporary local evidence storage operations, delayed synchronization operations, or alert communication operations according to communication quality conditions and contextual threat severity conditions associated with the transformer or the field infrastructure asset. In another embodiment, performing the adaptive evidence management further includes dynamically modifying image resolution, frame count, capture interval, monitoring persistence duration, or surveillance intensity according to the generated threat confidence level, temporal threat persistence analysis, or deployment resource conditions associated with the transformer or the field infrastructure asset.
The adaptive threat verification and surveillance orchestration workflow (300) illustrated in FIG. 3 is explained in greater detail below.
At step (302), the method includes monitoring operational conditions and security-related conditions associated with a transformer or a field infrastructure asset. In an embodiment, the operational conditions and security-related conditions may include electrical conditions, vibration conditions, tamper-related conditions, thermal conditions, movement-related conditions, positional conditions, enclosure interaction conditions, geofence-related conditions, or infrastructure security conditions associated with the transformer or the field infrastructure asset.
At step (304), the method includes detecting abnormal operational conditions or suspicious security-related events associated with the transformer or the field infrastructure asset. In an embodiment, abnormal operational conditions may include abnormal vibration patterns, unauthorized enclosure interaction, abnormal positional displacement, abnormal transformer interaction behavior, suspicious infrastructure interaction conditions, or recurring tamper-related conditions associated with the transformer or the field infrastructure asset.
At step (306), the method includes generating a primary threat indication corresponding to the detected abnormal operational conditions or suspicious security-related events. The generated primary threat indication activates contextual surveillance orchestration associated with the transformer or the field infrastructure asset.
At step (308), the method includes capturing contextual visual information associated with an environment surrounding the transformer or the field infrastructure asset. In an embodiment, the contextual visual information may include image information, movement information, enclosure interaction information, environmental interaction information, or human activity information associated with the transformer or the field infrastructure asset.
At step (310), the method includes performing secondary contextual threat verification using the contextual visual information and the primary threat indication. In an embodiment, the secondary contextual threat verification determines whether detected activity corresponds to genuine transformer threat activity or non-threatening activity associated with the transformer or the field infrastructure asset. The secondary contextual threat verification may differentiate maintenance-related interaction, authorized operational activity, incidental environmental movement, environmental disturbance, or operationally irrelevant activity from suspicious transformer interaction behavior associated with the transformer or the field infrastructure asset.
At step (312), the method includes generating a threat confidence level based on correlated operational-event intelligence and contextual visual information associated with the transformer or the field infrastructure asset. In an embodiment, the threat confidence level may be generated using correlated evaluation of vibration-related conditions, tamper-related conditions, movement-related conditions, enclosure interaction conditions, positional conditions, temporal event characteristics, and contextual visual conditions associated with the transformer or the field infrastructure asset.
In an embodiment, dynamically assigned weighted priority values may be allocated to operational-event intelligence and contextual visual information according to contextual threat severity associated with the transformer or the field infrastructure asset. Higher weighted priority values may be assigned to repeated tamper-related conditions, enclosure interaction conditions, abnormal positional displacement conditions, or recurring suspicious activity, whereas lower weighted priority values may be assigned to non-threatening environmental activity or incidental movement conditions associated with the transformer or the field infrastructure asset.
At step (314), the method includes performing temporal threat persistence analysis associated with recurring or progressively evolving suspicious activity associated with the transformer or the field infrastructure asset. In an embodiment, the temporal threat persistence analysis evaluates whether suspicious activity persists, recurs, or progressively evolves over a predefined time duration associated with the transformer or the field infrastructure asset. The temporal threat persistence analysis enables identification of recurring transformer threat conditions that may not be identifiable through isolated event analysis.
In an example embodiment, temporal threat persistence analysis may evaluate suspicious activity over predefined durations ranging between 30 seconds and 24 hours according to operational deployment conditions associated with the transformer or the field infrastructure asset.
At step (316), the method includes determining a surveillance escalation mode according to the generated threat confidence level and the temporal threat persistence analysis. In an example implementation, surveillance escalation mode (SE) may be dynamically determined according to:
SE=f(TC+TP+CQ)
where:
SE represents determined surveillance escalation mode,
TC represents generated threat confidence level,
TP represents temporal threat persistence information, and
CQ represents communication quality condition associated with the transformer or the field infrastructure asset.
In an embodiment, lower contextual threat severity conditions may activate snapshot capture operations, moderate contextual threat severity conditions may activate burst image capture operations, elevated contextual threat severity conditions may activate continuous monitoring operations, and critical contextual threat severity conditions may activate emergency surveillance transmission operations associated with the transformer or the field infrastructure asset.
At step (318), the method includes performing adaptive evidence management including alert transmission, temporary evidence storage, adaptive communication operations, or visual evidence transmission associated with the transformer or the field infrastructure asset. In an embodiment, adaptive evidence management selectively performs image transmission operations, image compression operations, temporary local evidence storage operations, delayed synchronization operations, or prioritized alert communication operations according to communication quality conditions, contextual threat severity conditions, or deployment resource conditions associated with the transformer or the field infrastructure asset.
In another embodiment, adaptive evidence management further includes dynamically modifying image resolution, frame count, image capture interval, monitoring persistence duration, or surveillance intensity according to generated threat confidence information, temporal threat persistence analysis, communication quality conditions, or deployment resource conditions associated with the transformer or the field infrastructure asset.
In an example embodiment, when abnormal vibration conditions and enclosure interaction conditions are detected near a transformer during non-operational hours, the method generates a primary threat indication and captures contextual visual information associated with the transformer environment. The method then performs secondary contextual threat verification to determine whether detected activity corresponds to maintenance-related activity or suspicious transformer interaction behavior. Upon determining elevated threat confidence information and recurring suspicious activity over time, the method dynamically activates continuous monitoring operations and prioritized evidence transmission operations. During reduced communication quality conditions, the method selectively performs temporary local evidence storage operations and delayed synchronization operations until communication conditions improve.
Figure 4 illustrates an example adaptive surveillance escalation workflow (400) associated with transformers and field infrastructure assets, according to one embodiment of the present invention. The workflow (400) enables adaptive surveillance response orchestration based on generated threat confidence information, temporal threat persistence analysis, communication quality conditions, and contextual threat severity conditions associated with transformers and field infrastructure assets deployed in geographically distributed and resource-constrained environments.
At step (402), the method includes receiving threat confidence level information and temporal persistence information associated with a transformer or a field infrastructure asset. In an embodiment, the received threat confidence level information may be generated based on correlated operational-event intelligence and contextual visual information associated with the transformer or the field infrastructure asset. The temporal persistence information may represent recurring suspicious activity, repeated operational anomalies, progressive tampering conditions, or prolonged suspicious transformer interaction behavior associated with the transformer or the field infrastructure asset.
At step (404), the method includes determining a threat severity condition based on the generated threat confidence level and the temporal threat persistence analysis associated with the transformer or the field infrastructure asset. In an embodiment, the threat severity condition may include a low threat severity condition, a medium threat severity condition, a high threat severity condition, or a critical threat severity condition associated with the transformer or the field infrastructure asset.
In an example implementation, threat severity condition (TS) may be dynamically determined according to:
TS=f(TC+TP+EV+CQ+RM)
where:
TS represents determined threat severity condition,
TC represents generated threat confidence level,
TP represents temporal threat persistence information,
EV represents operational-event severity information,
CQ represents communication quality condition, and
RM represents deployment resource management condition associated with the transformer or the field infrastructure asset.
In an embodiment, elevated threat confidence levels combined with recurring suspicious activity, elevated operational-event severity conditions, degraded communication quality conditions, or resource-constrained deployment conditions may increase the determined threat severity condition associated with the transformer or the field infrastructure asset.
At step (406), the method includes determining whether the threat severity condition is low. Upon determining the low threat severity condition, the method proceeds to step (408).
At step (408), the method includes performing snapshot capture operations associated with the transformer or the field infrastructure asset. In an embodiment, snapshot capture operations may include capturing a limited number of images, reduced monitoring persistence duration, reduced communication operations, reduced evidence transmission operations, or reduced surveillance intensity associated with the transformer or the field infrastructure asset.
In another aspect, when the threat severity condition is determined not to be low at step (406), the method proceeds to step (410).
At step (410), the method includes determining whether the threat severity condition is medium. Upon determining the medium threat severity condition, the method proceeds to step (412).
At step (412), the method includes performing burst image capture operations associated with the transformer or the field infrastructure asset. In an embodiment, burst image capture operations may include capturing multiple images over a predefined short-duration monitoring interval associated with the transformer or the field infrastructure asset to improve contextual threat verification and evidence collection operations.
In another aspect, when the threat severity condition is determined not to be medium at step (410), the method proceeds to step (414).
At step (414), the method includes determining whether the threat severity condition is high. Upon determining the high threat severity condition, the method proceeds to step (418).
At step (418), the method includes performing continuous monitoring operations and prioritized evidence transmission operations associated with the transformer or the field infrastructure asset. In an embodiment, continuous monitoring operations may include continuous image capture operations, elevated surveillance persistence duration, adaptive evidence prioritization operations, elevated communication priority operations, or continuous contextual monitoring operations associated with the transformer or the field infrastructure asset. In another aspect, when the threat severity condition is determined not to be high at step (414), the method proceeds to step (416).
At step (416), the method includes performing emergency surveillance transmission operations and persistent alert operations associated with the transformer or the field infrastructure asset. In an embodiment, emergency surveillance transmission operations may include high-priority alert communication operations, persistent evidence transmission operations, emergency monitoring activation operations, repeated alert communication operations, adaptive emergency surveillance escalation operations, or prioritized remote monitoring operations associated with the transformer or the field infrastructure asset.
At step (420), the method includes adaptively orchestrating surveillance response operations according to the determined threat severity condition associated with the transformer or the field infrastructure asset. In an embodiment, adaptive surveillance response orchestration includes dynamically modifying image resolution, frame count, monitoring persistence duration, capture interval, communication priority, evidence transmission operations, monitoring frequency, surveillance intensity, alert prioritization operations, or resource allocation operations according to contextual threat severity conditions, communication quality conditions, temporal persistence conditions, deployment resource conditions, or available power conditions associated with the transformer or the field infrastructure asset.
In another embodiment, when degraded communication quality conditions are detected, the workflow (400) selectively reduces image resolution, modifies transmission frequency, or activates temporary local evidence storage operations while preserving prioritized alert communication operations associated with the transformer or the field infrastructure asset.
In another embodiment, adaptive surveillance response orchestration further includes dynamically modifying surveillance persistence duration, monitoring frequency, or evidence transmission operations according to available power conditions associated with the transformer or the field infrastructure asset.
In an embodiment, the workflow (400) dynamically transitions between snapshot capture operations, burst image capture operations, continuous monitoring operations, and emergency surveillance transmission operations according to progressively evolving threat severity conditions associated with the transformer or the field infrastructure asset. The workflow (400) further supports adaptive escalation and adaptive de-escalation of surveillance response operations according to real-time contextual threat severity changes associated with the transformer or the field infrastructure asset.
In another embodiment, when contextual threat severity conditions reduce over time or suspicious activity is no longer detected, the workflow (400) dynamically de-escalates surveillance response operations from continuous monitoring operations to burst image capture operations or snapshot capture operations associated with the transformer or the field infrastructure asset.
In another embodiment, the workflow (400) further supports predictive surveillance escalation operations based on recurring suspicious activity patterns, repeated operational anomalies, or progressively evolving transformer interaction behavior associated with the transformer or the field infrastructure asset.
In an example embodiment, snapshot capture operations may include capturing one or more isolated images during lower threat severity conditions, burst image capture operations may include capturing multiple sequential images during moderate threat severity conditions, and continuous monitoring operations may include continuous image acquisition or periodic image acquisition during elevated threat severity conditions associated with the transformer or the field infrastructure asset.
In an example embodiment, when abnormal transformer enclosure interaction and recurring vibration-related conditions are detected during non-operational hours, the method determines an elevated threat confidence level and recurring suspicious activity associated with the transformer or the field infrastructure asset. Upon determining a medium threat severity condition, the method activates burst image capture operations for contextual threat verification. When suspicious activity progressively persists over time together with elevated tamper-related conditions, the method dynamically escalates surveillance response operations to continuous monitoring operations and prioritized evidence transmission operations. Upon further escalation to a critical threat severity condition, the method activates emergency surveillance transmission operations and persistent alert communication operations associated with the transformer or the field infrastructure asset. When the suspicious activity subsequently reduces and contextual threat severity conditions decrease, the method dynamically de-escalates surveillance operations to reduced monitoring operations associated with the transformer or the field infrastructure asset.
Figure 5 illustrates an example communication-aware adaptive evidence management workflow (500) associated with transformers and field infrastructure assets, according to one embodiment of the present invention. The workflow (500) enables adaptive communication orchestration, prioritized evidence transmission, temporary local evidence storage, delayed synchronization operations, resilient evidence preservation, and communication-aware surveillance management associated with transformers and field infrastructure assets deployed in geographically distributed and communication-constrained environments.
At step (502), the method includes receiving surveillance evidence information and threat severity information associated with a transformer or a field infrastructure asset. In an embodiment, the surveillance evidence information may include contextual visual information, captured image information, surveillance event information, threat confidence information, temporal persistence information, or prioritized alert information associated with the transformer or the field infrastructure asset.
At step (504), the method includes evaluating a communication quality condition associated with the transformer or the field infrastructure asset. In an embodiment, the communication quality condition may include network signal strength conditions, communication bandwidth conditions, communication latency conditions, communication stability conditions, communication availability conditions, or remote connectivity conditions associated with the transformer or the field infrastructure asset.
In an example implementation, communication response mode (CR) may be dynamically determined according to:
CR=f(CQ+TS+EP)
where:
CR represents determined communication response mode,
CQ represents communication quality condition,
TS represents threat severity condition, and
EP represents evidence priority condition associated with the transformer or the field infrastructure asset.
In an embodiment, elevated threat severity conditions together with reduced communication quality conditions may activate adaptive evidence prioritization operations, temporary local evidence storage operations, delayed synchronization operations, compressed evidence transmission operations, or fallback communication operations associated with the transformer or the field infrastructure asset.
At step (506), the method includes determining whether the communication quality condition is strong. Upon determining the communication quality condition as strong, the method proceeds to step (508).
At step (508), the method includes performing prioritized image transmission operations associated with the transformer or the field infrastructure asset. In an embodiment, prioritized image transmission operations may include high-resolution image transmission operations, prioritized surveillance evidence transmission operations, real-time alert communication operations, continuous evidence synchronization operations, or elevated communication priority operations associated with the transformer or the field infrastructure asset.
In another aspect, when the communication quality condition is determined not to be strong at step (506), the method proceeds to step (510). At step (510), the method includes determining whether the communication quality condition is moderate. Upon determining the communication quality condition as moderate, the method proceeds to step (512).
At step (512), the method includes performing compressed image transmission operations associated with the transformer or the field infrastructure asset. In an embodiment, compressed image transmission operations may include adaptive image compression operations, reduced-resolution image transmission operations, selective evidence transmission operations, reduced transmission frequency operations, or bandwidth-optimized surveillance communication operations associated with the transformer or the field infrastructure asset.
In another aspect, when the communication quality condition is determined not to be moderate at step (510), the method proceeds to step (514). At step (514), the method includes performing temporary local evidence storage operations and text-based alert communication operations associated with the transformer or the field infrastructure asset. In an embodiment, temporary local evidence storage operations may include local buffering of contextual visual information, delayed evidence storage operations, temporary surveillance evidence retention operations, adaptive evidence preservation operations, or resilient evidence buffering operations associated with the transformer or the field infrastructure asset.
In another embodiment, text-based alert communication operations may include transmission of threat alerts, prioritized warning messages, emergency notification information, operational alert information, reduced-bandwidth alert communication operations, or fallback communication operations associated with the transformer or the field infrastructure asset during degraded communication quality conditions.
At step (516), the method includes performing delayed synchronization operations upon communication network recovery associated with the transformer or the field infrastructure asset. In an embodiment, delayed synchronization operations may include deferred evidence transmission operations, prioritized synchronization operations, stored surveillance evidence recovery operations, adaptive communication restoration operations, historical evidence synchronization operations, evidence recovery operations, or retransmission validation operations associated with previously interrupted communication sessions.
In an example embodiment, communication quality conditions may include strong communication conditions associated with communication availability above 80%, moderate communication conditions associated with communication availability between 40% and 80%, and degraded communication conditions associated with communication availability below 40% associated with the transformer or the field infrastructure asset.
In another embodiment, the workflow (500) dynamically transitions between prioritized image transmission operations, compressed image transmission operations, temporary local evidence storage operations, and delayed synchronization operations according to real-time communication quality changes associated with the transformer or the field infrastructure asset.
In another embodiment, the workflow (500) further supports adaptive communication escalation and adaptive communication de-escalation according to contextual threat severity conditions and dynamically changing communication quality conditions associated with the transformer or the field infrastructure asset.
In another embodiment, communication-aware adaptive evidence management further includes dynamically modifying image resolution, transmission frequency, evidence prioritization level, synchronization interval, communication persistence duration, evidence buffering duration, or transmission priority according to contextual threat severity conditions, communication quality conditions, deployment resource conditions, or available power conditions associated with the transformer or the field infrastructure asset.
In another embodiment, the workflow (500) further supports fallback communication operations using alternative communication channels including cellular communication networks, low-bandwidth wireless communication networks, satellite communication networks, radio-frequency communication networks, or short-message-based communication operations according to communication quality conditions associated with the transformer or the field infrastructure asset.
In another embodiment, adaptive evidence management further includes secure evidence preservation operations, timestamp-based evidence association operations, or tamper-resistant evidence logging operations associated with the transformer or the field infrastructure asset.
In another embodiment, transmitted surveillance evidence information and operational-event information may further support remote maintenance verification operations, infrastructure inspection operations, maintenance activity validation operations, or operational diagnostics associated with the transformer or the field infrastructure asset.
In another embodiment, stored surveillance evidence information and operational-event history may be analyzed to identify recurring threat patterns, repeated infrastructure interaction behavior, operational anomaly trends, or dynamic infrastructure risk conditions associated with the transformer or the field infrastructure asset.
In another embodiment, the workflow (500) supports coordinated monitoring and communication-aware evidence management across geographically distributed transformers and field infrastructure assets deployed across multiple remote infrastructure locations. In another embodiment, prioritized alert communication operations further support utility response coordination operations, emergency dispatch operations, infrastructure protection operations, or remote security response operations associated with detected threat conditions.
In an example embodiment, when elevated threat severity conditions are detected during strong communication quality conditions, the workflow (500) performs prioritized high-resolution evidence transmission operations and real-time alert communication operations associated with the transformer or the field infrastructure asset. When communication quality conditions subsequently degrade to moderate communication conditions, the workflow (500) dynamically activates compressed image transmission operations and bandwidth-optimized evidence communication operations. Upon further degradation of communication quality conditions, the workflow (500) activates temporary local evidence storage operations and text-based alert communication operations while preserving critical threat alert communication associated with the transformer or the field infrastructure asset. Upon restoration of communication network conditions, the workflow (500) performs delayed synchronization operations to transmit stored surveillance evidence information associated with the transformer or the field infrastructure asset.
In an example real-world implementation, the disclosed adaptive intelligent surveillance system may be installed with transformers located in remote areas, utility power distribution locations, industrial sites, rural infrastructure locations, or other field infrastructure environments where theft, tampering, or unauthorized access may occur. During normal operation, the monitoring subsystem continuously monitors conditions such as vibration, enclosure opening, movement, temperature, or physical interaction associated with the transformer or the field infrastructure asset. When abnormal vibration, suspicious enclosure interaction, unauthorized movement, or tamper-related conditions are detected, the system generates a primary threat indication and activates contextual visual verification operations. The adaptive intelligent surveillance subsystem then captures contextual visual information around the transformer or the field infrastructure asset and verifies whether the detected activity corresponds to genuine threat activity or normal activity such as authorized maintenance operations or environmental movement.
In another example implementation, when suspicious activity continues for a prolonged duration or repeated abnormal conditions are detected, the system dynamically increases surveillance operations from snapshot image capture to burst image capture, continuous monitoring, or emergency surveillance transmission according to the determined threat severity conditions associated with the transformer or the field infrastructure asset. During weak or unstable communication conditions, the system may compress captured images, temporarily store evidence locally, transmit only prioritized alerts, or perform delayed synchronization until communication conditions improve. Once communication connectivity is restored, the stored surveillance evidence may be transmitted to a remote monitoring platform for operator review, maintenance support, security verification, or infrastructure protection operations. Through adaptive monitoring, contextual threat verification, adaptive surveillance escalation, and communication-aware evidence management, the disclosed invention enables reliable protection of transformers and field infrastructure assets in remote and communication-constrained deployment environments.
In an embodiment, the disclosed system may be retrofitted with existing transformer monitoring infrastructure without requiring replacement of deployed monitoring systems.
A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims. ,CLAIMS:We Claim:
1. A method for adaptive intelligent surveillance of transformers and field infrastructure assets, the method comprising:
monitoring, by a monitoring subsystem, one or more operational conditions and security-related conditions associated with a transformer or a field infrastructure asset;
detecting, by the monitoring subsystem, an abnormal operational condition or a suspicious security-related event associated with the transformer or the field infrastructure asset;
generating, by the monitoring subsystem, a primary threat indication corresponding to the detected abnormal operational condition or suspicious security-related event;
activating, by an adaptive intelligent surveillance subsystem communicatively coupled with the monitoring subsystem, a contextual visual verification operation in response to the generated primary threat indication;
capturing, by the adaptive intelligent surveillance subsystem, contextual visual information associated with an environment surrounding the transformer or the field infrastructure asset;
performing, by the adaptive intelligent surveillance subsystem, secondary contextual threat verification using the contextual visual information and the primary threat indication;
generating, by the adaptive intelligent surveillance subsystem, a threat confidence level based on correlated evaluation of the primary threat indication and the contextual visual information;
determining, by the adaptive intelligent surveillance subsystem, a surveillance escalation mode according to the generated threat confidence level; and
performing, by the adaptive intelligent surveillance subsystem, adaptive evidence management according to the determined surveillance escalation mode and one or more communication quality conditions associated with the transformer or the field infrastructure asset.

2. The method as claimed in claim 1, wherein performing the secondary contextual threat verification comprises determining whether detected activity corresponds to genuine transformer threat activity or non-threatening activity associated with the transformer or the field infrastructure asset.

3. The method as claimed in claim 1, wherein generating the threat confidence level comprises correlating operational-event intelligence, contextual visual information, tamper-related conditions, vibration-related conditions, movement-related conditions, enclosure interaction conditions, or temporal event characteristics associated with the transformer or the field infrastructure asset.

4. The method as claimed in claim 3, wherein generating the threat confidence level further comprises assigning weighted priority values to the operational-event intelligence and the contextual visual information for dynamically determining contextual threat severity associated with the transformer or the field infrastructure asset.

5. The method as claimed in claim 1, further comprising performing temporal threat persistence analysis based on recurring suspicious activity, repeated operational anomalies, progressive tampering conditions, or prolonged transformer interaction behavior associated with the transformer or the field infrastructure asset.

6. The method as claimed in claim 1, wherein determining the surveillance escalation mode comprises dynamically selecting at least one of a snapshot capture mode, burst image capture mode, continuous monitoring mode, emergency surveillance transmission mode, adaptive reporting mode, or prioritized evidence transmission mode according to the generated threat confidence level and the temporal threat persistence analysis.

7. The method as claimed in claim 1, wherein performing the adaptive evidence management comprises selectively performing image transmission operations, image compression operations, temporary local evidence storage operations, delayed synchronization operations, or alert communication operations according to communication quality conditions and contextual threat severity conditions associated with the transformer or the field infrastructure asset.

8. The method as claimed in claim 1, wherein performing the adaptive evidence management further comprises dynamically modifying image resolution, frame count, capture interval, monitoring persistence duration, or surveillance intensity according to the generated threat confidence level, temporal threat persistence analysis, or deployment resource conditions associated with the transformer or the field infrastructure asset.

9. A system for adaptive intelligent surveillance of transformers and field infrastructure assets, the system comprising:
a monitoring subsystem configured to monitor one or more operational conditions and security-related conditions associated with a transformer or a field infrastructure asset and generate a primary threat indication corresponding to a detected abnormal operational condition or suspicious security-related event; and
an adaptive intelligent surveillance subsystem communicatively coupled with the monitoring subsystem and configured to:
perform contextual visual verification in response to the generated primary threat indication;
capture contextual visual information associated with an environment surrounding the transformer or the field infrastructure asset;
perform secondary contextual threat verification using the contextual visual information and the primary threat indication; generate a threat confidence level based on correlated evaluation of the primary threat indication and the contextual visual information;
determine a surveillance escalation mode according to the generated threat confidence level; and
perform adaptive evidence management according to the determined surveillance escalation mode and one or more communication quality conditions associated with the transformer or the field infrastructure asset.

10. The system as claimed in claim 9, wherein the adaptive intelligent surveillance subsystem is further configured to:
perform temporal threat persistence analysis associated with suspicious activity detected in relation to the transformer or the field infrastructure asset;
assign weighted priority values to operational-event intelligence and contextual visual information for dynamically determining contextual threat severity associated with the transformer or the field infrastructure asset;
selectively perform snapshot capture operations, burst image capture operations, continuous monitoring operations, emergency surveillance transmission operations, adaptive reporting operations, temporary local evidence storage operations, adaptive image compression operations, delayed synchronization operations, or prioritized alert communication operations according to contextual threat severity conditions, communication quality conditions, or deployment resource constraints associated with the transformer or the field infrastructure asset; and
differentiate genuine transformer threat activity from non-threatening activity associated with the transformer or the field infrastructure asset.