Description:
FIELD OF THE INVENTION
The present invention relates to the field of power distribution systems, specifically to low voltage (LV) network monitoring solutions. It involves the integration of Internet of Things (IoT) technology to facilitate predictive maintenance and remote monitoring of LV network components such as cables, feeder pillars, and fuses. The invention is particularly applicable to utilities and electricity distribution companies, industrial/commercial electrical facilities seeking to enhance operational efficiency, reduce maintenance costs, and improve the reliability of power supply through advanced monitoring and data analytics.

Application of the Invention
The invention is designed for use in power distribution utilities and electrical facilities, providing a comprehensive monitoring and control solution for LV networks. By employing a plug-and-fit approach with compact sensor nodes and Bluetooth communication, the invention enables real-time monitoring of network parameters such as voltage, current, temperature, and energy consumption. The data collected is transmitted to a central node and further to a cloud-based platform for analysis and visualization via a web GUI. This facilitates predictive maintenance, reduces downtime, and enhances customer satisfaction by ensuring a reliable power supply. The cost-effective and scalable nature of the solution makes it suitable for widespread deployment in various power distribution settings.

BACKGROUND OF THE INVENTION
In the realm of power distribution, low voltage (LV) networks are critical for delivering electricity to end-users. These networks, comprising cables, feeder pillars, and fuses, operate at 415 volts and are prone to various challenges such as load imbalances, harmonics, overloads, and power theft. Traditionally, maintenance of these networks has been reactive, addressing failures as they occur, which leads to increased operational costs and reduced reliability of power supply. The need for a more proactive approach, such as predictive maintenance, is evident to enhance the efficiency and reliability of LV networks.

Prior Art Problems
Existing solutions for monitoring LV networks are often complex and expensive, making them impractical for widespread adoption. The current market offerings are characterized by bulky designs, difficult installation processes, and high costs, which hinder scalability and efficiency. Additionally, manual monitoring methods are labour-intensive and prone to human error, further exacerbating the challenges faced by power distribution utilities.

Prior Art Disadvantages
1. High Costs: The cost of existing monitoring solutions is prohibitive, limiting their deployment across extensive LV networks.
2. Bulky Design: The large size of current devices makes installation challenging, especially in space-constrained environments like feeder pillars.
3. Complex Installation: The intricate installation process requires significant time and expertise, adding to operational expenses.
4. Limited Scalability: Due to the aforementioned factors, scaling these solutions to cover entire networks is not feasible.

Problem Statement
There is a pressing need for a cost-effective, compact, and easy-to-install solution for monitoring LV networks that can overcome the limitations of existing technologies and provide reliable, real-time data for predictive maintenance.

Technical Solution of the Present Invention
The present invention offers an IoT-based solution for LV network monitoring, featuring compact sensor nodes that are easy to install and communicate wirelessly via Bluetooth. Each sensor node is equipped with a current transformer and thermocouple for precise energy and temperature measurements. The data collected is transmitted to a central node, which aggregates the information and sends it to a cloud-based platform for analysis. This setup allows for real-time monitoring and predictive maintenance, significantly reducing downtime and operational costs.

Technical Effect
The invention enables comprehensive remote monitoring of LV networks, providing utilities with actionable insights to prevent failures and optimize maintenance schedules. The compact design and wireless communication reduce installation time and complexity, while the cost-effective nature of the solution makes it accessible for widespread deployment.

Technical Advancement Over the Prior Art
1. Cost Reduction: The invention significantly lowers the cost per sensor node, making it feasible to deploy across large networks.
2. Compact Design: The sensor nodes are designed to be small and unobtrusive, fitting easily within existing infrastructure.
3. Ease of Installation: The plug-and-fit approach and wireless communication eliminate the need for extensive wiring, reducing installation time significantly.
4. Scalability: The solution is designed to be scalable, allowing utilities to expand monitoring capabilities as needed.

Need for the Present Invention
The present invention addresses the critical need for an efficient, scalable, and cost-effective solution for LV network monitoring. By leveraging IoT technology, it provides utilities with the tools necessary to transition from reactive to predictive maintenance, enhancing the reliability of power supply and reducing operational costs. This innovation is essential for modernizing power distribution systems and meeting the growing demand for reliable electricity.

OBJECT OF THE INVENTION
The primary object of the invention is to provide a low voltage (LV) network monitoring solution that is cost-effective, compact, and easy to install, thereby overcoming the limitations of existing technologies. The invention aims to:
1. Enhance Predictive Maintenance: Enable real-time monitoring of LV network parameters such as voltage, current, temperature, and energy consumption to facilitate predictive maintenance and reduce downtime.
2. Reduce Operational Costs: Offer a solution that significantly lowers the cost per sensor node, making it economically viable for widespread deployment across extensive LV networks.
3. Simplify Installation: Provide a plug-and-fit design with wireless communication capabilities to minimize installation time and complexity, allowing for rapid deployment even in space-constrained environments.
4. Improve Network Reliability: Increase the reliability of power supply by providing utilities with actionable insights to prevent failures and optimize maintenance schedules.
5. Scalability and Flexibility: Design a solution that is scalable and adaptable to various power distribution settings, enabling utilities to expand monitoring capabilities as needed.
6. Enhance Customer Satisfaction: By reducing downtime and improving the reliability of power supply, the invention aims to enhance customer satisfaction and support revenue growth for utilities.

Through these objectives, the invention seeks to modernize LV network monitoring and provide a practical, efficient solution for power distribution utilities.

SUMMARY OF THE INVENTION
The following disclosure presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. This summary is not an extensive overview of the present invention. It is not intended to identify the key/critical elements of the invention or to delineate the scope of the invention. Its sole purpose is to present some concept of the invention in a simplified form as a prelude to a more detailed description of the invention presented later.

The present invention provides an innovative Internet of Things (IoT) solution for monitoring low voltage (LV) networks, addressing the challenges of cost, complexity, and scalability associated with existing technologies. The invention is designed to facilitate predictive maintenance and enhance the reliability of power distribution systems by offering a compact, cost-effective, and easy-to-install monitoring solution.

Aspects and Implementations
1. Compact Sensor Nodes: The invention features sensor nodes that are compact in size, having appropriate desirable measurement . These nodes are equipped with a current transformer and thermocouple for accurate energy and temperature measurements, achieving at least good accuracy.
2. Wireless Communication: Each sensor node communicates wirelessly via Bluetooth, eliminating the need for extensive wiring and simplifying the installation process. This wireless setup allows for seamless data transmission to a central node.
3. Central Node and Data Aggregation: The central node, mounted on the feeder pillar wall, collects data from multiple sensor nodes. It is equipped with additional sensors, such as a water level sensor and a door sensor, to monitor environmental conditions.
4. Cloud-Based Data Analysis: The central node transmits the aggregated data to a cloud-based platform using the MQTT protocol. This platform provides a web GUI for real-time data visualization and analysis, enabling utilities to make informed decisions for predictive maintenance.
5. Plug-and-Fit Design: The invention's design emphasizes ease of installation, with a plug-and-fit approach that reduces installation time. This feature is particularly beneficial in space-constrained environments like feeder pillars.
6. Cost-Effectiveness: The solution is designed to be economically viable. This affordability makes it feasible for utilities to deploy the solution across extensive LV networks.
7. Scalability and Flexibility: The invention is scalable, allowing utilities to expand monitoring capabilities as needed. It is adaptable to various power distribution settings, making it suitable for a wide range of applications in the utilities sector.
8. Enhanced Reliability and Customer Satisfaction: By providing real-time monitoring and predictive maintenance capabilities, the invention enhances the reliability of power supply, reduces downtime, and improves customer satisfaction.

Through these aspects and implementations, the invention offers a comprehensive solution for modernizing LV network monitoring, addressing the critical needs of power distribution utilities, and supporting the transition to more efficient and reliable power systems.

Thus, in accordance with an aspect of the present invention there is provided a system for monitoring a low voltage (LV) network, comprising:

a plurality of sensor nodes, each sensor node configured to measure parameters of network elements, including voltage, current, temperature, energy, and, power quality parameter wherein each sensor node comprises:
 a compact current transformer for precise energy measurement;
 a thermocouple for temperature measurement;
 a power supply;
 a processor configured for edge computing;
 Bluetooth communication for wireless data transmission;
 a printed circuit board (PCB);

a central node mounted on a feeder pillar wall, configured to receive data from the plurality of sensor nodes, the central node comprising:
 a water level sensor;
 a door sensor;
 Narrowband Internet of Things (NB-IoT)/ GSM communication for transmitting collated data to a central server;
 Bluetooth communication to collect data from all the sensor nodes; and
 Power Supply

a central server configured to receive and analyze data from the central node, providing insights into network performance and facilitating predictive maintenance;

wherein the system is characterized by a plug-and-fit approach, rugged design, ingress protection, compact size, and cost-effectiveness, enabling remote monitoring and reducing installation time.

In accordance with another aspect of the present invention there is provided a method for monitoring a low voltage (LV) network, comprising the steps of:
o deploying a plurality of sensor nodes within the LV network, each sensor node configured to measure parameters of network elements;
o utilizing a compact current transformer and a thermocouple within each sensor node to obtain precise electrical and temperature measurements, respectively;
o powering each sensor node with a power supply and processing data using a processor configured for edge computing;
o transmitting the measured data wirelessly from each sensor node to a central node using Bluetooth communication;
o mounting the central node on a feeder pillar wall, the central node configured to receive and collate data from the plurality of sensor nodes;
o equipping the central node with a water level sensor and a door sensor for additional monitoring capabilities;
o transmitting the collated data from the central node to a central server using Narrowband Internet of Things (NB-IoT)/ GSM communication;
o analyzing the received data at the central server to provide insights into network performance and facilitate predictive maintenance;

wherein the method is characterized by a plug-and-fit approach, rugged design, ingress protection, compact size, and cost-effectiveness, enabling remote monitoring and reducing installation time.

Other aspects, advantages, and salient features of the invention will become apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the annexed drawings, discloses exemplary embodiments of the invention.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The accompanying figures illustrate various aspects and embodiments of the integral spacer for the pole assembly of an air circuit breaker, as described in the present invention. These figures are provided to enhance the understanding of the invention and are not intended to limit its scope.

FIG. 1: Sensor Node Components
This figure illustrates the components of a sensor node used in the low voltage network monitoring system. It includes a power supply unit converting 240V to 3.3V, an energy measurement IC, temperature sensing components, a Bluetooth IC for wireless communication, a thermocouple for temperature measurement, and a custom-made 400 Amp current transformer for energy measurement. The setup is designed to facilitate precise monitoring of network parameters.

FIG. 2: Feeder Pillar with Node Placement
This figure depicts the physical setup of a feeder pillar, highlighting the strategic placement of sensor nodes within the low voltage network. The nodes are shown attached to the cables, enabling wireless communication with the cloud, represented by the label "C." This setup allows for real-time data transmission and monitoring without extensive wiring.

FIG. 3: Central Node Components
This figure presents the components of the central node, which serves as the data aggregation hub in the monitoring system. It includes a power supply unit (240V/4V/3.3V), a Bluetooth IC for communication with sensor nodes, a GSM module for data transmission to the cloud, and inputs for a water level sensor and a door sensor. These components enable comprehensive monitoring and secure data transmission.

FIG. 4: System Architecture
This figure illustrates the overall architecture of the low voltage network monitoring solution. It shows a typical 4-way feeder pillar with circuits (Ckt-1 to Ckt-4) equipped with sensor nodes. The central node collects data from these nodes via Bluetooth and transmits it to the cloud using the MQTT protocol. The cloud platform provides a web GUI for real-time data visualization and analysis, supporting informed decision-making for predictive maintenance. The color-coded lines (R, Y, B) represent different electrical phases within the pillar.

DETAILED DESCRIPTION OF THE INVENTION
The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of various embodiments of the present disclosure 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 various embodiments described herein can be made without departing from the scope and spirit of the present disclosure. In addition, descriptions of well-known functions and constructions may be omitted for clarity and conciseness.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments belong. Further, the meaning of terms or words used in the specification and the claims should not be limited to the literal or commonly employed sense but should be construed in accordance with the spirit of the disclosure to most properly describe the present disclosure.

The terminology used herein is for the purpose of describing particular various embodiments only and is not intended to be limiting of various embodiments. As used herein, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising" used herein specify the presence of stated features, integers, steps, operations, members, components, and/or groups thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, members, components, and/or groups thereof.

The present disclosure will now be described more fully with reference to the accompanying drawings, in which various embodiments of the present disclosure are shown.

The present invention is an IoT-based solution designed to monitor low voltage (LV) networks, providing a comprehensive approach to predictive maintenance and enhancing the reliability of power distribution systems. The invention comprises several key components and embodiments, each contributing to its overall functionality and effectiveness.

Embodiments of the Invention
Sensor Nodes: The core of the invention is the sensor nodes, which are compact devices having appropriate dimensions. Each node is equipped with:

The sensor nodes are a pivotal component of the invention, designed to provide precise monitoring of low voltage (LV) network parameters. These nodes are engineered to be compact, efficient, and easy to install, making them ideal for deployment across extensive LV networks. Below is an elaborate description of their construction, functionality, and integration within the system.

Constructional Features

1. Compact Design: Each sensor node is designed with a small footprint, having appropriate dimensions. This compact size allows for easy installation in space-constrained environments, such as within feeder pillars.
2. Current Transformer: The sensor node includes a current transformer that measures the current flowing through the network. This component is crucial for detecting load imbalances and potential overloads, providing real-time data on electrical load conditions.
3. Thermocouple: Integrated within the sensor node is a thermocouple, which accurately measures the temperature of network components. This feature helps identify overheating issues that could lead to equipment failures, allowing for timely intervention.
4. Bluetooth Module: A Bluetooth communication module is embedded in each sensor node, enabling wireless data transmission to the central node. This wireless capability eliminates the need for extensive wiring, simplifying installation and reducing costs.
5. Power Supply: The sensor nodes are designed to be energy-efficient, consuming optimum power. This low power consumption ensures prolonged operation and reduces the need for frequent maintenance or battery replacements.

Functional Interrelations

• Data Acquisition: The sensor nodes continuously monitor key parameters such as current and temperature. This data is crucial for assessing the health and performance of the LV network.
• Wireless Communication: The Bluetooth module facilitates seamless wireless communication with the central node. This setup allows for real-time data transmission without the complexities associated with wired connections.
• Integration with Central Node: The sensor nodes are strategically placed within the network to ensure comprehensive coverage. They communicate with the central node, which aggregates the data and transmits it to the cloud platform for further analysis.

Best Mode of Operation
The sensor nodes are best deployed in areas of the LV network that are prone to faults or require close monitoring. Their compact design and wireless communication capabilities make them ideal for installation in existing infrastructure without significant modifications. The nodes should be configured to operate continuously, providing real-time data to the central node and cloud platform.

Implementation in the System
1. Installation: The sensor nodes are installed at critical points within the LV network using a plug-and-fit approach. This method ensures quick and easy deployment, even in confined spaces.
2. Configuration: Once installed, the sensor nodes are configured to communicate with the central node via Bluetooth. This setup ensures that data is transmitted efficiently and reliably.
3. Data Monitoring: The nodes continuously monitor network parameters, providing real-time insights into the network's performance and health.
4. Data Transmission: The collected data is wirelessly transmitted to the central node, which aggregates the information and sends it to the cloud platform for analysis.

By integrating these sensor nodes into the LV network, the invention provides a robust and scalable solution for real-time monitoring and predictive maintenance, enhancing the reliability and efficiency of power distribution systems.

Central Node:
The central node is a crucial component of the invention, serving as the primary data aggregation and communication hub within the low voltage (LV) network monitoring system. It is designed to collect, process, and transmit data from multiple sensor nodes to a cloud-based platform, enabling real-time monitoring and analysis. Below is an elaborate description of its construction, functionality, and integration within the system.

Constructional Features

1. Robust Housing: The central node is housed in a durable enclosure designed to withstand environmental conditions typically found in power distribution settings. This includes protection against dust and moisture, ensuring reliable operation over time.

2. Data Collection Interface: The central node is equipped with a sophisticated data collection interface that receives data from multiple sensor nodes via Bluetooth. This interface is designed to handle simultaneous data streams, ensuring efficient aggregation of information.

3. Additional Sensors: To enhance monitoring capabilities, the central node includes additional sensors such as:

o Water Level Sensor: Monitors the presence of water within the feeder pillar, which could indicate potential flooding or moisture ingress.
o Door Sensor: Detects unauthorized access or tampering with the feeder pillar, providing an additional layer of security.

4. Communication Module: The central node features a communication module that transmits aggregated data to a cloud-based platform using the MQTT protocol. This module ensures secure and reliable data transmission over the network.

5. Power Supply: The central node is designed to operate efficiently with a stable power supply, ensuring continuous operation and data transmission.

Functional Interrelations

• Data Aggregation: The central node collects data from all connected sensor nodes, aggregating the information for comprehensive analysis. This process involves filtering and organizing the data to ensure accuracy and relevance.

• Environmental Monitoring: The additional sensors provide critical environmental data, such as water levels and access status, which are integrated into the overall monitoring system to enhance situational awareness.

• Data Transmission: The communication module ensures that the aggregated data is transmitted to the cloud platform in real-time. This transmission is secure and efficient, leveraging the MQTT protocol for reliable data delivery.

Best Mode of Operation

The central node is best positioned within the feeder pillar, where it can maintain optimal communication with all sensor nodes. It should be configured to operate continuously, ensuring that data is collected and transmitted without interruption. The node's robust design and additional sensors make it well-suited for deployment in various environmental conditions.

Implementation in the System
1. Installation: The central node is mounted on the feeder pillar wall, strategically positioned to ensure effective communication with all sensor nodes. Its installation is straightforward, requiring minimal modifications to existing infrastructure.

2. Configuration: Once installed, the central node is configured to establish communication with the sensor nodes and the cloud platform. This involves setting up the Bluetooth connections and configuring the MQTT protocol for data transmission.

3. Data Processing: The central node continuously collects data from the sensor nodes, processing and aggregating the information for transmission. This includes integrating environmental data from the additional sensors.

4. Data Transmission: The processed data is transmitted to the cloud platform, where it is stored and analyzed. The central node ensures that data is sent in real-time, providing utilities with up-to-date insights into network conditions.

By integrating the central node into the LV network monitoring system, the invention provides a robust and scalable solution for data aggregation and transmission, supporting real-time monitoring and predictive maintenance of power distribution systems.

The central node in the present invention plays a crucial role in the overall system architecture by acting as a hub for data collection and transmission. It utilizes Narrowband Internet of Things (NB-IoT) or GSM communication technology to transmit collated data from the sensor nodes to a central server. This choice of communication protocol offers several advantages that are particularly beneficial for monitoring low voltage (LV) networks.

Cloud-Based Platform: The cloud platform is responsible for data storage, analysis, and visualization. It provides:

o Web GUI: A user-friendly interface for real-time monitoring and analysis of network parameters.
o Data Analytics: Tools for predictive maintenance, allowing utilities to optimize maintenance schedules and prevent failures.

Constructional and Functional Interrelations

• Sensor Nodes and Central Node: The sensor nodes are strategically placed within the LV network to monitor critical parameters. They communicate wirelessly with the central node, which aggregates the data and ensures seamless transmission to the cloud platform.
• Central Node and Cloud Platform: The central node acts as a bridge between the sensor nodes and the cloud platform. It collects data from the nodes, processes it, and sends it to the cloud for further analysis and visualization.
• Cloud Platform and User Interface: The cloud platform processes the data and presents it through a web GUI, enabling utilities to monitor network conditions in real-time and make informed decisions for maintenance and optimization.

Best Mode of Working

The best mode of working involves deploying the sensor nodes in feeder pillar, particularly in areas prone to faults or failures. The central node should be strategically positioned inside the feeder pillar to ensure optimal communication with all sensor nodes. The cloud platform should be configured to provide real-time data analysis and alerts, enabling utilities to respond promptly to any anomalies detected in the network.

Detailed Description of Method and Implementation

1. Installation: The sensor nodes are installed at each outgoing feeder within the feeder pillar LV network using a plug-and-fit approach. The central node is mounted on the feeder pillar wall, and all components are configured for wireless communication.
2. Data Collection: The sensor nodes continuously monitor parameters such as voltage, current, and temperature. This data is transmitted wirelessly to the central node.
3. Data Aggregation and Transmission: The central node aggregates data from all sensor nodes and transmits it to the cloud platform using the MQTT protocol. The additional sensors on the central node provide environmental data, enhancing the overall monitoring capability.
4. Data Analysis and Visualization: The cloud platform processes the data and presents it through a web GUI. Utilities can access this interface to monitor network conditions, receive alerts, and analyze trends for predictive maintenance.
5. Predictive Maintenance: Based on the data analysis, utilities can schedule maintenance activities proactively, reducing downtime and improving network reliability.

By implementing this method, the invention provides a robust solution for LV network monitoring, addressing the challenges of cost, complexity, and scalability, and supporting the transition to more efficient and reliable power distribution systems.

Central Server:
o Data Analysis and Reporting: The central server is a pivotal component of the IoT solution for monitoring low voltage (LV) networks, serving as the primary data processing and analysis hub. Its role is to transform raw data collected from the network into actionable insights that enhance network performance and reliability. Here's an elaborate description of its functions and benefits:

Data Reception and Integration:

1. Data Aggregation: The central server receives collated data from the central node, which has already gathered information from multiple sensor nodes distributed throughout the LV network. This data includes critical parameters such as voltage, current, temperature, energy, and power quality parameters, as well as additional inputs from sensors like water level and door sensors.

2. Seamless Integration: The server is designed to integrate seamlessly with existing network management systems, allowing for a unified view of the network's performance. This integration ensures that data from the IoT solution can be combined with other operational data, providing a comprehensive overview of the network's status.

Data Analysis and Insights:

1. Real-Time Processing: The central server is equipped with advanced data processing capabilities that enable real-time analysis of incoming data. This immediate processing allows for the quick identification of trends, anomalies, and potential issues within the network.

2. Predictive Analytics: By employing sophisticated algorithms and machine learning techniques, the server can perform predictive analytics. This involves analyzing historical and current data to forecast future network conditions and identify potential issues before they manifest as failures. For example, the server can detect patterns indicative of load imbalances, overheating, or component degradation.

3. Insight Generation: The analysis performed by the central server generates valuable insights into network performance. These insights can include efficiency metrics, reliability assessments, and recommendations for optimizing network operations. The server can also provide visualizations and reports that make it easier for network operators to understand and act on the data.

Facilitating Predictive Maintenance:

1. Issue Identification: One of the key benefits of the central server's analysis capabilities is its ability to identify potential issues early. By recognizing signs of wear, stress, or failure in network components, the server enables proactive maintenance actions.

2. Downtime Reduction: By facilitating predictive maintenance, the server helps reduce network downtime. Addressing issues before they lead to failures minimizes disruptions to the power supply, enhancing customer satisfaction and operational efficiency.

3. Improved Reliability: The insights provided by the central server contribute to improved network reliability. By maintaining optimal network conditions and preventing unexpected outages, the system ensures a consistent and dependable power supply.

Operational Efficiency and Decision Support:

1. Resource Optimization: The server's analysis helps optimize resource allocation for maintenance and operations. By prioritizing maintenance tasks based on the severity and likelihood of issues, utilities can allocate their resources more effectively.

2. Strategic Planning: The data-driven insights from the central server support strategic planning and decision-making. Utilities can use this information to plan network expansions, upgrades, and other long-term initiatives with greater confidence.

In summary, the central server is a critical component of the IoT solution, transforming raw data into actionable insights that enhance the performance and reliability of LV networks. By facilitating predictive maintenance and providing comprehensive analysis, the server plays a vital role in reducing downtime, improving reliability, and supporting efficient network management.

Method of Operation:

The method of monitoring the LV network using the system involves several key steps:

1. Deployment of Sensor Nodes: The method begins with deploying a plurality of sensor nodes within the LV feeder pillar. Each node is strategically placed to measure parameters of network elements, including voltage, current, temperature, energy, and power quality parameters.
2. Data Collection and Processing: The sensor nodes utilize their compact current transformers and thermocouples to obtain precise energy and temperature measurements. The data is processed locally using the node's processor configured for edge computing.
3. Wireless Data Transmission: The processed data is transmitted wirelessly from each sensor node to the central node using Bluetooth communication. This step minimizes wiring complexity and facilitates quick installation.
4. Data Collation and Transmission: The central node receives and collates data from the sensor nodes. It uses NB-IoT or GSM communication to transmit the collated data to the central server for further analysis.
5. Data Analysis and Predictive Maintenance: The central server analyzes the received data to provide insights into network performance. It identifies potential issues and facilitates predictive maintenance, reducing downtime and improving reliability.

Scalability and Integration:

The system is designed to be scalable, allowing additional sensor nodes to be integrated as the network expands. This scalability makes it suitable for a wide range of applications, from small-scale installations to large utility networks. Furthermore, the system can be integrated with existing network management systems, providing seamless data exchange and enhancing operational efficiency.

Installation Process for Low Voltage Network Monitoring System

1. Current Transformer (CT) Installation:
o Secure the custom-made current transformer on the Z-strip within the feeder pillar. Ensure that the CT is properly aligned and securely fastened to prevent any movement that could affect measurement accuracy.
o Verify the correct polarity of the CT connections to ensure accurate current readings. This step is crucial for detecting load imbalances and potential overloads in the network.
2. PCB Mounting:
o Attach the printed circuit board (PCB) to the CT mounted on the Z-strip. Ensure that the PCB is aligned correctly and securely fastened to maintain a stable connection.
o The PCB should be positioned to allow easy access to the Bluetooth IC and other components for maintenance and troubleshooting.
3. Power Supply Connection:
o Tap the required power supply directly from the busbar to power the sensor node. Ensure that the power supply is stable and provides the necessary voltage conversion (240V to 3.3V) for the sensor node components.
o Implement proper insulation and safety measures to prevent electrical hazards and ensure reliable operation.
4. Central Node Installation:
o Mount the central node securely on the feeder pillar side wall. The central node should be positioned to maintain optimal communication with all sensor nodes within the pillar.
o Ensure that the central node is protected from environmental factors such as dust and moisture, which could affect its performance.
5. Sensor Node Configuration:
o Configure each sensor node to communicate wirelessly with the central node via Bluetooth. This setup eliminates the need for extensive wiring and simplifies the installation process.
o Verify that each sensor node is functioning correctly and transmitting data to the central node.
6. Central Node Configuration:
o Configure the central node to receive data from all connected sensor nodes and transmit the aggregated data to the cloud platform using the GSM module or NB-IoT communication.
o Ensure that the central node's additional sensors, such as the water level sensor and door sensor, are operational and integrated into the monitoring system.

7. System Testing and Verification:
o Conduct a comprehensive system test to verify that all components are functioning correctly and that data is being transmitted accurately to the cloud platform.
o Check the web GUI for real-time data visualization and ensure that the system provides actionable insights for predictive maintenance.

By following this installation process, the low voltage network monitoring system can be deployed efficiently, providing utilities with a robust solution for real-time monitoring and predictive maintenance. The plug-and-fit design and wireless communication capabilities significantly reduce installation time and complexity, making the system suitable for widespread deployment.

DESCRIPTION OF THE FIGURES

FIG. 1: Sensor Node Components
This figure provides a detailed view of the components that make up a sensor node in the low voltage network monitoring system. The sensor node is designed to be compact and efficient, facilitating precise monitoring of network parameters. Key components include:
• Power Supply (240/3.3V): Converts the incoming 240V AC to 3.3V DC, providing the necessary power for the sensor node's electronic components.
• Energy Measurement IC: Responsible for accurately measuring energy consumption and other electrical parameters within the network.
• Temperature Sensing Components: These components, including a thermocouple, measure the temperature of network elements, helping to identify potential overheating issues.
• Bluetooth IC: Enables wireless communication between the sensor node and the central node, eliminating the need for extensive wiring.
• Custom Made Current Transformer: Measures the current flowing through the network, providing data on load conditions and potential imbalances.
• 240 V Input: The primary power input for the sensor node, which is converted to the required voltage levels for operation.

FIG. 2: Feeder Pillar with Node Placement
This figure illustrates the physical setup of a feeder pillar, showcasing the strategic placement of sensor nodes within the low voltage network. The feeder pillar is a critical component of the power distribution system, housing various electrical circuits and connections. Key elements include:
• Sensor Nodes: Shown as small devices attached to the cables within the feeder pillar. Each node monitors specific parameters such as voltage, current, and temperature.
• Wireless Communication Pathway: Indicated by the label "C" for cloud connectivity, this pathway allows for data transmission from the sensor nodes to the cloud without extensive wiring.
• Feeder Pillar Structure: The internal structure of the feeder pillar is depicted, providing context for the placement of sensor nodes and their role in monitoring the network.
• Environmental Protection: The design of the feeder pillar and the placement of nodes are intended to protect against environmental factors such as dust and moisture, ensuring reliable operation.

FIG. 3: Central Node Components
This figure presents the components of the central node, which serves as the data aggregation hub in the monitoring system. The central node is designed to collect, process, and transmit data from multiple sensor nodes to a cloud-based platform. Key components include:
• Power Supply: Provides the necessary power for the central node's operation, converting the incoming voltage to suitable levels for its components.
• Bluetooth IC: Facilitates communication with sensor nodes, allowing the central node to receive data wirelessly.
• GSM Module: Enables data transmission from the central node to the cloud platform, ensuring secure and reliable communication.
• Water Level Sensor Input: Monitors the presence of water within the feeder pillar, indicating potential flooding or moisture ingress.
• Door Sensor Input: Detects unauthorized access or tampering with the feeder pillar, providing an additional layer of security.

FIG. 4: System Architecture
This figure illustrates the overall architecture of the low voltage network monitoring solution, detailing the interaction between various components and the flow of data. Key elements include:
• Typical 4-Way Pillar: Depicts a typical setup with circuits labeled as Ckt-1, Ckt-2, Ckt-3, and Ckt-4, each equipped with sensor nodes for monitoring electrical parameters.
• Central Node: Positioned centrally within the pillar, it collects data from all sensor nodes via Bluetooth and serves as the aggregation point for data before transmission to the cloud.
• Communication Pathways: Shows the data flow from the central node to the cloud using the MQTT protocol, essential for real-time data transmission and analysis.
• Cloud and Web GUI: The cloud platform is depicted as the destination for data, where it is stored and analyzed. The web GUI provides a user-friendly interface for utilities to access and interpret the data, enabling informed decision-making.
• Color-Coded Phases: The circuits within the pillar are color-coded (R, Y, B) to represent different electrical phases, aiding in understanding the distribution of sensor nodes across the network.

These figures collectively provide a comprehensive view of the invention's physical setup and system architecture, illustrating how the components interact to achieve effective LV network monitoring and predictive maintenance.

ADVANTAGES OF THE PRESENT INVENTION
The present invention offers several advantages over traditional monitoring systems for low voltage (LV) networks, addressing key challenges and providing significant improvements in efficiency, cost-effectiveness, and reliability. The advantages include:

1. Cost-Effectiveness: The invention provides a highly cost-effective solution for monitoring LV networks. By utilizing compact and efficient sensor nodes, the system significantly reduces the overall cost of deployment and maintenance compared to traditional systems.

2. Compact Design: The sensor nodes are designed with a compact form factor, allowing them to be easily installed in space-constrained environments such as feeder pillars. This compact design also contributes to the system's cost-effectiveness and ease of installation.

3. Ease of Installation: The plug-and-fit approach of the system minimizes installation time and complexity. The use of wireless communication, such as Bluetooth, reduces the need for extensive wiring, allowing for quick and straightforward setup.

4. Scalability: The system is designed to be scalable, enabling additional sensor nodes to be integrated as the network expands. This scalability makes the solution suitable for a wide range of applications, from small-scale installations to large utility networks.

5. Energy Efficiency: Each sensor node is powered by a supply that consumes a minimum power, ensuring energy-efficient operation. This low power consumption is particularly beneficial for large-scale deployments.

6. Predictive Maintenance: By providing real-time monitoring and data analysis, the system facilitates predictive maintenance, allowing potential issues to be identified and addressed before they lead to failures. This reduces downtime and enhances the reliability of the power supply.

7. Enhanced Reliability: The system's ability to monitor critical network parameters such as voltage, current, temperature, energy, and power quality parameters ensures that the LV network operates reliably and efficiently, reducing the risk of outages and improving customer satisfaction.

8. Rugged and Durable Design: The system is designed to be resistant to dust and water ingress. This rugged design ensures durability and reliable performance even in harsh environmental conditions.

9. Integration with Existing Systems: The invention can be integrated with existing network management systems, providing seamless data exchange and enhancing operational efficiency. This integration capability allows utilities to leverage their current infrastructure while benefiting from the advanced features of the new system.

10. Comprehensive Monitoring: The inclusion of additional sensors, such as water level and door sensors, in the central node provides comprehensive monitoring capabilities, further enhancing the system's utility and effectiveness.

Overall, the present invention represents a significant advancement in the field of power distribution monitoring, offering a practical, scalable, and efficient solution that addresses the limitations of traditional systems.

The descriptions and illustrations provided in this document are intended to explain the principles of the invention and its best mode of working. They are not intended to limit the scope of the invention, which is defined by the claims. Variations and modifications to the described embodiments may be made without departing from the scope of the invention. The specific embodiments described in this document are examples of the invention and are not intended to limit the scope of the claims. The claims should be interpreted broadly to cover all equivalent structures and methods that fall within the scope of the invention. The technical specifications and details provided in this document are for illustrative purposes only. Actual implementations of the invention may vary based on specific design requirements, manufacturing processes, and application needs.

Any references to prior art documents, patents, or publications are provided for informational purposes only. The inclusion of such references does not imply that the present invention is limited by or dependent on the prior art.
, Claims:
1. A system for monitoring a low voltage (LV) network, comprising:
a plurality of sensor nodes, each sensor node configured to measure parameters of network elements, including voltage, current, temperature, energy, and few power quality parameters , wherein each sensor node comprises:
 a compact current transformer for precise energy measurement;
 a thermocouple for temperature measurement;
 a power supply;
 a processor configured for edge computing;
 Bluetooth communication for wireless data transmission;
 a printed circuit board (PCB);

a central node mounted on a feeder pillar wall, configured to receive data from the plurality of sensor nodes, the central node comprising:
 a water level sensor;
 a door sensor;
 NB-IoT or GSM communication for transmitting collated data to a central server;
 Bluetooth communication to collect data from all the sensor nodes; and
 Power Supply

a central server configured to receive and analyze data from the central node, providing insights into network performance and facilitating predictive maintenance;

wherein the system is characterized by a plug-and-fit approach, rugged design, ingress protection, compact size, and cost-effectiveness, enabling remote monitoring and reducing installation time.

2. The system of claim 1, wherein the sensor nodes are configured to detect and report load imbalances and power theft occurrences within the LV network.

3. The system of claim 1, wherein the central node is further configured to process data from the sensor nodes to identify potential faults or failures in the network.

4. The system of claim 1, wherein the Bluetooth communication in each sensor node is optimized to minimize wiring complexity and facilitate quick installation.

5. The system of claim 1, wherein the central node is configured to send real-time alerts to a remote monitoring system upon detecting abnormal network conditions.

6. The system of claim 1, wherein the compact current transformer in each sensor node achieve precise accuracy for energy measurements.

7. The system of claim 1, wherein the thermocouple in each sensor node provides real-time temperature data to prevent overheating and potential damage to network components.

8. The system of claim 1, wherein the central node includes a user interface for local monitoring and configuration of the sensor nodes.

9. The system of claim 1, wherein the NB-IoT or GSM communication in the central node is optimized for low power consumption and extended range, ensuring reliable data transmission to the central server.

10. The system of claim 1, wherein the ingress protection of ensures the system is resistant to dust and water ingress, enhancing its durability and longevity.

11. The system of claim 1, wherein the system is scalable, allowing additional sensor nodes to be integrated to accommodate network expansion.

12. The system of claim 1, wherein the system is designed to integrate with existing network management systems, providing seamless data exchange and enhanced operational efficiency.

13. The system of claim 1, wherein the system includes a diagnostic tool for troubleshooting and maintenance, enabling quick identification and resolution of issues.

14. The system of claim 1, wherein the system is configured to provide analytics and reporting capabilities, offering insights into network performance and facilitating data-driven decision-making.

15. The system of claim 1, wherein the central server is configured to store historical data for trend analysis and long-term network performance evaluation.

16. A method for monitoring a low voltage (LV) network, comprising the steps of:
o deploying a plurality of sensor nodes within the LV network, each sensor node configured to measure parameters of network elements;
o utilizing a compact current transformer and a thermocouple within each sensor node to obtain precise energy and temperature measurements, respectively;
o powering each sensor node with a power supply and processing data using a processor configured for edge computing;
o transmitting the measured data wirelessly from each sensor node to a central node using Bluetooth communication;
o mounting the central node on a feeder pillar wall, the central node configured to receive and collate data from the plurality of sensor nodes;
o equipping the central node with a water level sensor and a door sensor for additional monitoring capabilities;
o transmitting the collated data from the central node to a central server using Narrowband Internet of Things (NB-IoT) or GSM communication;
o analyzing the received data at the central server to provide insights into network performance and facilitate predictive maintenance;

wherein the method is characterized by a plug-and-fit approach, rugged design, ingress protection, compact size, and cost-effectiveness, enabling remote monitoring and reducing installation time.

17. The method of claim 16, wherein the network elements, including voltage, current, temperature, energy, and few power quality parameters

18. The method of claim 16, wherein the power supply consuming a minimum of power in milliwatt.

19. The method of claim 16, further comprising the step of detecting and reporting load imbalances and power theft occurrences within the LV network using the sensor nodes.

20. The method of claim 16, further comprising the step of processing data at the central node to identify potential faults or failures in the network.

21. The method of claim 16, wherein the step of transmitting data wirelessly from each sensor node is optimized to minimize wiring complexity and facilitate quick installation.

22. The method of claim 16, further comprising the step of sending real-time alerts from the central node to a remote monitoring system upon detecting abnormal network conditions.

23. The method of claim 16, further comprising the step of calibrating the compact current transformer in each sensor node to achieve accurate energy measurements.

24. The method of claim 16, further comprising the step of providing real-time temperature data from the thermocouple in each sensor node to prevent overheating and potential damage to network components.

25. The method of claim 16, further comprising the step of providing a user interface at the central node for local monitoring and configuration of the sensor nodes.

26. The method of claim 16, wherein the NB-IoT or GSM communication in the central node is optimized for low power consumption and extended range, ensuring reliable data transmission to the central server.

27. The method of claim 16, wherein the ingress protection ensures the system is resistant to dust and water ingress, enhancing its durability and longevity.

28. The method of claim 16, further comprising the step of scaling the system by integrating additional sensor nodes to accommodate network expansion.

29. The method of claim 16, further comprising the step of facilitating the installation process with a user-friendly interface and step-by-step instructions, reducing the need for specialized technical skills.

30. The method of claim 16, further comprising the step of integrating the system with existing network management systems, providing seamless data exchange and enhanced operational efficiency.

31. The method of claim 16, further comprising the step of utilizing a diagnostic tool for troubleshooting and maintenance, enabling quick identification and resolution of issues.