DESC:FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
The Patent Rules, 2003
COMPLETE SPECIFICATION
(See sections 10 & rule 13)
TITLE OF THE INVENTION
AN IOT BASED SMART SYSTEM FOR CATTLE/ COW HEALTH AND OESTROUS CYCLE MONITORING
2. APPLICANT (S)
NAME NATIONALITY ADDRESS
DIVYASAMPARK IHUB ROORKEE FOR DEVICES MATERIALS AND TECHNOLOGY FOUNDATION IN Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India.
3. PREAMBLE TO THE DESCRIPTION
COMPLETE SPECIFICATION

The following specification particularly describes the invention and the manner in which it is to be performed.

FIELD OF INVENTION:
[001] The present invention relates to the field of animal health monitoring system. The present invention in particular relates to an IoT (Internet of Things), based system and method for cattle/ cow health and Oestrous cycle monitoring.
DESCRIPTION OF THE RELATED ART:
[002] In the prior art systems, attempts have been made to use an ovarian monitor for in home measurement ofestrone glucuronide (E1G) and pregnanediol glucuronide (PdG). Blackwell L.F., et al.,Steroids 68:465-476 (2003), incorporated by reference herein. In this study, the results from the Ovarian Monitor were compared to results obtained from radio immunoassays. It was reported that in 50% of the cycles a urine bias in the ovarian monitor test caused a delay of up to 3 days in identifying the beginning of the E1G rise compared with the radioimmunoassay, which was reported as being more reliable. Id. at 469. The E1G values obtained using the monitor were higher than those obtained by RIA, and this was reported as being attributed to a vertical displacement of the profiles resulting from a bias caused by interfering substances in the relatively large volumes of urine and the prolonged incubation times required for obtaining the necessary sensitivity of the assay. Id, at 474.
[003] There is a need for better in-home and on-site fertility status assays that rivals the accuracy of assays performed in clinical settings, and which are simple, convenient, and cost effective. The use of quantitative strips offers a more flexible system for on-site and home fertility care than Monitors such as described in Blackwell L.F., et ah, Id, which although accurate suffer from the disadvantage of not having the ease of use provided by a quantitative strip system such as described here in. Such assays would provide considerable savings and enable accurate and cost-effective daily monitoring of ovarian activity. Additionally, a quantitative home assay kit with improved accuracy over other strip systems is needed. The inventions herein address these and other needs.
[004] Reference may be made to the following:
[005] Publication No. IN2090/KOLNP/2008 relates to methods of monitoring the ovulation cycle of an animal by detecting specific analytes in body fluids, computer program products, devices, data processing systems, and kits for monitoring the ovulation cycle and determining the fertility of female mammals.
[006] Publication No. CN201905123 relates to a cow oestrus monitoring system, which is characterized by comprising at least one acceleration detection unit mounted on a cow. The acceleration detection units are connected with a step analyzing unit so as to obtain and analyze cow walking information, the step analyzing unit is connected with a wireless communication transmitting unit, the wireless communication transmitting unit is connected with a wireless communication receiving unit in a wireless mode, and the wireless communication receiving unit is connected with a upper computer so as to store the cow walking information and analyzing current state of the cow by the aid of preset program.
[007] Publication No. CN202890184 discloses a cow oestrus detecting system. The cow oestrus detecting system is characterized by comprising a sensing module, a storage and calculation module, a communication module and a system analysis module, wherein the sensing module is an acceleration sensor which is used for collecting movement of a cow and conducts quantization collection on the movement of the cow. The storage and calculation module is a single chip microcomputer and is used for storing data which is collected by a comparison sensing module in real time, implementing alarming and sending the data to an upper computer in a fixed time. The communication module is used for communication between the single chip microcomputer and the upper computer.
[008] Publication No. WO2005104930 relates to the remote animal health and location monitoring system includes an implantable/wearable monitoring device. The monitoring device includes a housing. The housing includes a plurality of sensors configured for sampling one or more predetermined conditions of the animal. The housing further contains a monitoring device controller in communication with the sensors for receiving signals indicative of the conditions. A monitoring device transmitter is in communication with the sensors for receiving signals indicative of the conditions. A monitoring device transmitter is in communication with the monitoring device controller and configured for transmitting or broadcasting transmitter signals as sensed by the sensors. The monitoring device further includes a power source in communication with the sensors, controller and transmitter.
[009] Publication No. EP2999407 relates to sensor apparatuses for attachment to an animal that include a housing and a sensor assembly. The housing can be attachable to the animal and includes an internal cavity formed therein. The sensor assembly can be disposed within the internal cavity of the housing. The sensor assembly includes a force sensor and an accelerometer arranged to detect force data and accelerometer data representative of a physiological state of the animal. Exemplary embodiments are also directed to method and sensor systems for detecting a physiological state of an animal.
[010] Publication No. CN219146437 relates to a cow health remote monitoring device which comprises a supporting rod and a supporting plate, the supporting plate is fixedly installed on the inner side of the supporting rod, the supporting rod and the supporting plate are installed in a single cow house, and the cow health remote monitoring device further comprises a health monitoring mechanism used for remotely monitoring cow health, the health monitoring mechanism is installed on the supporting plate, the health monitoring mechanism comprises a transparent protection box body and a wide-angle camera, and the beneficial effects are that the wireless pedometer is arranged to record the number of movement steps of the dairy cow, the infrared temperature sensor is arranged to monitor the body temperature change of the dairy cow, and the health monitoring mechanism is arranged on the supporting plate and comprises a transparent protection box body and a wide-angle camera.
[011] Publication No. CN117061562 relates to an intelligent cow monitoring platform and device based on an intelligent pasture, and the platform comprises a data collection assembly and a terminal upper computer which are connected through a wireless transmission module. The data acquisition assembly comprises an STM32 chip, a storage module, a GPS positioning sensor, a motion sensor and a temperature sensor. A monitoring function on cows in a pasture is realized through the data acquisition assembly, cow movement information acquired by the data acquisition assembly is transmitted to the terminal upper computer through the wireless transmission module, and upper computer software can display data of each sensor in real time.
[012] Publication No. CN111067484 discloses a dairy cow physiological parameter external behavior intelligent monitoring system and method. The intelligent monitoring system is characterized by comprising a sensing layer, a network layer, a cloud platform, an operation layer and a service layer, wherein the sensing layer is used for monitoring behavior parameters of a dairy cow in real time; the network layer transmits data monitored by the sensing layer to the cloud platform; the cloud platform shares data to the operation layer through middleware; and the service layer acquires data by accessing the operation layer. According to the invention, electronic devices such as an intelligent sensing chip, an indicator lamp and the like are adopted to monitor the physiological parameter external behavior of the dairy cow (the activity amount of the dairy cow and the climbing and collapsing behavior of the dairy cow), the intelligent monitoring device is worn on the dairy cow to collect the activity amount and the climbing data of the dairy cow and upload the activity amount and the climbing and collapsing data of the dairy cow to the platform, the condition of the activity amount and the climbing and collapsing data of the dairy cow (oestrus detection accuracy reaches 90% or above) is obtained through large data analysis, and workers are informed to know oestrus and health conditions of the dairy cow in time through an APP to carry out accurate positioning.
[013] Publication No. CN110728268 provides a cow rumination behavior recognition method based on a decision tree classifier and a noseband pressure envelope signal, and belongs to the technical field of animal individual sign monitoring. The rumination behavior can monitor the estrus, the eating condition, the physical sign health condition and the like of cows and other livestock with rumination physiological behaviors.
[014] Publication No. CN110710469 discloses a device for detecting cow activity and body temperature, which belongs to the technical field of detection, and mainly consists of a temperature sensor, a wireless communication module, a microcontroller, a pedometer chip and a storage module. The device is characterized in that the temperature sensor and the wireless communication module are connected with the microcontroller, and the microcontroller is connected with the pedometer chip and the storage module. The device can accurately and effectively monitor the change of cow body temperature and activity, is helpful for timely determining reproductive states and health conditions of cows such as estrus, pregnancy and the like, and prevents diseases, shortens calving intervals, improves milk yield and improves economic benefits of dairy farms through a scientific and timely management technology.
[015] Publication No. CN207665013 relates to an embodiment of the utility model provides a milk cow information acquisition device belongs to the electronic equipment field. Milk cow information acquisition device acquires the sound sound signal of milk cow through electret microphone to thereby the information of ruminating that corresponding processing obtained the milk cow is carried out to each module through among the mobile module, the amount of exercise information of milk cow is acquired through the milk cow pedometer to information of ruminating and the amount of exercise information of long -range host computer accessible milk cow are foreseeing that the milk cow estruses and the health provides reliable foundation, and then monitor the health of milk cow, have improved cow breeding's convenience.
[016] Publication No. CN107103554 discloses a cow intelligent monitoring method and system. The method comprises the steps: collecting the biological information and features of a cow group, wherein the biological information comprises the body temperature, pulse, amount of exercise and sleep duration data, and the biological features comprises the oestrum features, ill features, health features and suckling period features; taking the biological information as the input, taking the biological features as the output, and building a cow state classification model through a supporting vector machine algorithm; collecting the real-time biological information of a single cow; inputting the real-time biological information into the cow state classification model, and obtaining a classification result, wherein the classification result comprises the oestrum, ill period, healthy period and suckling period of the cow.
[017] Publication No. CN205794463 discloses a remote monitoring milk cow health and system of oestrusing, it relates to dairy product production technical field. Its centralized storage computer and monitor terminal connect, herds of cattle information radio signal reception ware and centralized storage computer link, the other district of milking that is equipped with of herds of cattle information radio signal reception ware, milk the district and the feeding area lead to through the passageway that hives off, it is equipped with the door that hives off on the passageway to hive off, the door that hives off links to each other with an electrical drive part that hives off, the passageway that hives off still links there is another passageway, another passageway leads to has the situation cattle pen to put the district, hive off the door in the junction of hiving off passageway and another passageway, there is a neck ring on the milk stubbornness, the neck ring top is fixed and is equipped with an inductor, be equipped with three dimensions motion sensor in the inductor, the micro processor, the memory, the ox code sets up and the radio signal generator.
[018] Publication No. US2008066685 relates to a milk temperature monitor helps determine the health or physiological condition of a lactating animal (e.g., cow, goat, sheep, camel, etc.). It does this by comparing the temperature of the animal's milk to an acceptable temperature range that is automatically adjusted to compensate for a varying ambient air temperature. In some embodiments, the acceptable temperature range is adjusted based on the average milk temperature reading of the most recent series of animals that were milked. The average reading is preferably a rolling average of a limited sample size. In calculating the rolling average, the monitor disregards temperature readings that are beyond a reasonable range.
[019] Publication No. NZ502231 relates to monitoring the exhalation of livestock, domestic animals and poultry can provide information on the health, diet or other condition of the animal. Condition can be determined from a component of the exhalation, which may be an odour specific compound or other material. It is therefore important that any monitoring is based on an accurately taken sample. schematically in part-sectional form an animal condition monitor for collecting the sample from the nostril of, for example, a cow. The body of the monitor is an inert, transparent plastic tube, which is free from odours and easily cleaned. The ends of the tube can be closed in a gas-tight manner by closures and to enclose a space.
[020] The article entitled “Cattle health monitoring system using wireless sensor network: a survey from innovation perspective” by Bhisham Sharma, Deepika Koundal; IET Wireless Sensor Systems Volume 8, Issue 4 Pages 143-151; 01 August 2018 talks about the wireless sensor network (WSN)-based automatic health monitoring systems for monitoring various diseases of dairy cattle. The main objective of WSN-based intelligent monitoring systems in farm automation is to monitor the health of dairy cattle on regular basis. This monitoring system needs to be installed in local and remote locations of farms that will assist the concerned farmers in monitoring their cattle activities from diverse locations for the whole day. All collected factors from the automated system will be stored in a database. Subsequently, with the help of farm automation, farmers can retrieve information for the execution of correct farm control strategies. Moreover, WSN is low-cost technology which is specific for the identification of diseases in dairy animals. This revolution in advanced technological farm automation will aid in improving the productivity rate with the reduction of human intervention.
[021] The article entitled “IoT based tracking cattle health monitoring system using wireless sensors” by Jai Ganesh Rajendran, Manjunathan Alagarsamy, Vaishnavi Seva, Paramathi Mani Dinesh, Balamurugan Rajangam, Kannadhasan Suriyan; Bulletin of Electrical Engineering and Informatics Vol. 12, No. 5 pp. 3086~3094; October 2023 talks about the wireless sensor-based automated dairy cow health monitoring systems. The fundamental purpose of wireless sensor network (WSN) based smart surveillance systems in agricultural optimization is to follow the health of dairy cows on a continual basis. This monitoring gadget must be installed in both local and remote farm areas so that interested farmers may monitor their cattle's movements throughout the day from several places. The data collected by the automated system would be kept in a database. Farmers may then obtain data using farm automation to execute effective farm management techniques. Furthermore, WSN is a low-cost device created exclusively for identifying illnesses in dairy cows. This achievement in sophisticated technology agricultural automation would assist to boost productivity by reducing human involvement.
[022] Similar technologies exist in health tracking wearables for cattle or humans; however, they either focus on individual metrics (like body temperature or motion) or require manual processes to detect Oestrous cycles.
[023] In order to overcome above listed prior art, the present invention aims to provide an IoT based system and method for cow health and Oestrous cycle monitoring. The system tracks temperature, behavior, or milk yield but fail to integrate real-time multi-sensor data (e.g., audio, accelerometer, gyroscope, temperature, and rumination data) for both health and reproductive monitoring. Present invention is a multi-sensor system including temperature, movement, rumination, and vocalization data with AI-driven analytics and voice recognition to deliver a holistic solution for monitoring the oestrus cycle and overall cow health.
OBJECTS OF THE INVENTION:
[024] The principal object of the present invention is to provide a IoT based smart cow/ cattle health and Oestrous cycle monitoring system and method.
[025] Another object of the present invention is to provide a system which increases productivity, enhances animal welfare, and reduces manual effort in monitoring large herds.
[026] Still another object of the present invention is to provide a system which tracks temperature, behavior, and/ or milk yield.
[027] Yet another object of the present invention is to provide a system which integrating real-time multi-sensor data for both health and reproductive monitoring.
SUMMARY OF THE INVENTION:
[028] The present invention relates to the IoT based smart system for cattle/ cow’s health and oestrous cycle monitoring. The system comprises IoT sensors and machine learning method to predict Oestrous cycles and monitor overall health. The system automatically classifies cow vocalizations with machine learning to detect heat periods. The system includes a fusion of real-time accelerometer, gyroscope, temperature, and rumination data for health monitoring and predicts both health issues and Oestrous cycles through a unified platform.
[029] The system integrates the data on a custom-built dashboard with automated alerts and detailed reporting, accessible through a mobile device. The proposed IoT-based smart system for cattle health and oestrous cycle Monitoring integrates multiple sensors and machine learning technologies to deliver a real-time, comprehensive monitoring solution.
BREIF DESCRIPTION OF THE INVENTION
[030] It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered for limiting of its scope, for the invention may admit to other equally effective embodiments.
[031] Figure 1 shows cattle/ cow’s health and oestrous cycle monitoring system;
[032] Figure 2 shows flowchart according to the present invention.
DETAILED DESCRIPTION OF THE INVENTION:
[033] The present invention provides an IoT based smart system for cattle/ cow’s health and oestrous cycle monitoring. The system comprises IoT sensors (1, 2, 3,), control unit (4) and machine learning method to predict Oestrous cycles and monitor overall health. The system uses five different sensors, including:
• Audio sensors (1) to detect cow vocalizations (MFCC features help classify cow sounds related to heat periods).
• Temperature sensors (2) to monitor body temperature.
• Accelerometer and gyroscope sensors (3) to track body movement.
[034] The IoT-based smart system for cow health and oestrous cycle monitoring integrates five key components.
[035] IoT Sensors (1, 2, 3) includes-
a) Audio Sensor (1): Captures cow vocalizations. These sounds are stored in the storage unit (5) and later processed using MFCC features to detect vocal indicators of the oestrous cycle.
b) Temperature Sensor (2): Continuously measures the cow's body temperature, helping identify health anomalies or heat symptoms.
c) Accelerometer and Gyroscope Sensors (3): Monitor body movements and activity patterns that signal behavioral changes during oestrus or illness.
[036] Control Unit (4) including central hub that receives data from all sensors. It communicates wirelessly with cloud storage and a mobile dashboard and interfaces with the machine learning algorithm to analyze incoming data.
[037] Storage Unit (5) stores all sensor data (especially audio) for real-time or later analysis. It supports local SD card or cloud-based data storage.
[038] Machine Learning Module processes audio features (MFCCs), temperature, movement, and rumination data. It detects patterns indicating health status and oestrous cycles and triggers alerts and notifications for farmers and veterinarians.
[039] The system comprises control unit with audio sensors to capture and save cow vocalization data in SD card or cloud storage (5), which is later processed using Mel Frequency Cepstral Coefficients (MFCC) features to classify sounds and predict the oestrous cycle. Temperature Sensors monitors changes in body temperature, a critical parameter for detecting health issues and oestrous periods. Accelerometer and Gyroscope Sensors to track movement and activity patterns, providing insights into behavioral changes related to health and reproduction.
[040] Data from these sensors are collected and processed using machine learning algorithms. Combines real-time data from multiple sensors to ensure accurate and reliable predictions for oestrous cycles and health conditions. Train on historical datasets to classify and predict conditions such as heat periods, post-insemination phases, and potential health anomalies.
[041] Audio sensors record cow sounds, saved to an SD card/cloud (5), and analyze them using MFCC features to detect heat-related vocalizations. Temperature sensors track body heat changes, signaling health issues or oestrus. Accelerometer/ gyroscope monitor movement patterns (e.g., restlessness during heat). Machine learning combines all sensor data to predict oestrous cycles and health problems, trained on past data for accuracy.
[042] Sensor data is continuously captured and can be transmitted wirelessly to the system. MFCC features are extracted from audio data to classify cow vocalizations. Other sensors provide temperature, movement, and activity pattern.
[043] Machine learning models analyze combined features to predict Oestrous cycles for optimal insemination timing and health anomalies, enabling early intervention.
[044] The sensors continuously send data wirelessly to the system. MFCCs convert cow sounds into numerical features for analysis. Temperature, motion, and activity data are combined. ML models predict the best time for insemination (oestrus) and detect illnesses early.
[045] Processed data is visualized on a dashboard. A machine learning model is integrated into the system to provide real-time predictions based on the incoming data. Alerts and reports are generated and accessible on mobile devices for farm managers and veterinarians.
[046] The processed data is stored on cloud securely for future analysis and comparison.
[047] Thus the system integrates data from audio, accelerometer, gyroscope and temperature sensors. This combination provides a holistic understanding of the cow’s health and reproductive state.
[048] The system employs machine learning algorithms to process complex multi-sensor data in real-time. A dashboard shows real-time health/reproductive status. ML models process live data and send alerts to mobile devices. All data is securely stored in the cloud for future review combining audio, motion, and temperature data for full health insights.
[049] The inclusion of MFCC features for audio analysis is a unique approach, enabling precise classification of cow sounds to predict heat periods.
[050] By leveraging IoT technology, the system ensures real-time data collection and processing, providing instant alerts for health issues or oestrous cycles. MFCCs (usually for human speech) are adapted to classify cow sounds accurately. IoT enables instant data processing and alerts for heat/health issues. This reduces manual effort and enhances response times.
[051] The invention supports cloud-based data storage, allowing secure and remote access to historical data. It also integrates seamlessly with a mobile dashboard for user convenience.
[052] The combination of sensor fusion and AI enables proactive health monitoring, ensuring early detection of potential issues and timely management of breeding cycles.
[053] The system automatically classifies cow vocalizations with machine learning to detect heat periods. The system includes a fusion of real-time accelerometer, gyroscope, temperature, and rumination data for health monitoring and predicts both health issues and Oestrous cycles through a unified platform. The system integrates the data on a custom-built dashboard with automated alerts and detailed reporting, accessible through a mobile device.
[054] It reduces manual checks by automating monitoring. Cloud storage lets farmers access data remotely. Mobile dashboard provides easy monitoring. Sensor fusion with AI detects problems early, improving breeding success.
[055] The collected data is processed in real-time to predict heat periods, health issues, and post-insemination conditions using trained machine learning models. This system also enables data visualization on a dashboard through a Flutter app, ensuring farm managers and veterinarians can monitor each cow's status remotely.
[056] The system alerts when cows enter the Oestrous cycle for optimal insemination timing. ML models predict heat cycles, health issues, and post-insemination status. Flutter dashboard lets vets/farmers check cow health remotely. Alerts notify when cows are in heat for optimal breeding timing.
[057] It tracks real-time health metrics to detect anomalies early, improving herd management and stores the data securely on a cloud-based platform or storage device for future analysis. This system increases productivity, enhances animal welfare, and reduces manual effort in monitoring large herds.
[058] The invention builds on IoT (Internet of Things), machine learning models, and real-time health monitoring systems, the system tracks temperature, behavior, or milk yield and integrates real-time multi-sensor data (e.g., audio, accelerometer, gyroscope, temperature, and rumination data) for both health and reproductive monitoring. Tracks real-time health data (temp, movement, rumination). Cloud storage keeps records for future analysis. Boosts productivity by reducing manual labor and improving animal care. It uses IoT with ML to merge sensor data for smarter farming.
[059] This system leverages sensor fusion, MFCC features from cow audio data, and machine learning models to provide real-time, comprehensive insights into both the health and Oestrous cycle of cows, automating the prediction process.
[060] Hence this IoT-based smart system for cattle health and oestrous cycle monitoring bridges the gap in existing technologies by integrating a multi-sensor approach with AI-driven analytics. Its real-time monitoring, predictive capabilities, and user-friendly interface make it a distinct and invaluable solution for improving productivity, enhancing animal welfare, and reducing manual effort in herd management.
[061] Figure 2 shows the flowchart. The flowchart illustrates the step-by-step operation of the system. System initializes and sensors activate. All three types of sensor data are collected continuously. MFCCs and numerical features are extracted from raw data. Features are sent to the control unit and stored in local/cloud storage. Data is processed using a trained ML model. Health issues, heat periods, or post-insemination phases are identified. Real-time info displayed on mobile dashboard. Automated alerts for farm management actions. The data is saved securely for future use. The stepwise workflow includes-
a) Attach sensors to cows (e.g., audio mic on collar).
b) Sensors log data every 5–10 mins (configurable).
c) Control unit timestamps and merges data streams.
d) Pre-emphasis ? Framing ? FFT ? Mel filterbank ? DCT.
e) Compact feature vector representing vocalizations.
f) Input: [MFCCs, Temp, Activity Score, Rumination Rate] ? Output: Prediction.
g) Combines mfccs and elevated body temperature with increased restlessness (from accelerometer data).
h) Flags deviations in rumination or activity patterns and temp that suggest illness or stress.
i) Stores data in cloud storage ? Enables trend analysis (e.g., "Heat cycles per cow over 6 months").
[062] Numerous modifications and adaptations of the system of the present invention will be apparent to those skilled in the art, and thus it is intended by the appended claims to cover all such modifications and adaptations which fall within the true spirit and scope of this invention.
,CLAIMS:WE CLAIM:
1. An IoT based smart system for cattle/ cow’s health and oestrous cycle monitoring comprises-
a) IoT sensors (1, 2, 3, 4) characterized in that audio sensors (1) to detect cow vocalizations; temperature sensors (2) to monitor body temperature; accelerometer and gyroscope sensors (3) to track body movement;
b) control unit (4) with communication interface and machine learning method to predict Oestrous cycles and monitor overall health based on the sensor data continuously captured and transmitted wirelessly to the system wherein integrated machine learning model provides real-time predictions based on the incoming data. Alerts and reports are generated and accessible on mobile devices for farm managers and veterinarians;
c) storage (5) unit to save cow vocalization data which is later processed using Mel Frequency Cepstral Coefficients (MFCC) features to classify sounds and predict the oestrous cycle.
2. The IoT based smart system for cattle/ cow’s health and oestrous cycle monitoring, as claimed in claim 1, wherein the machine learning model includes following steps.
a) All five sensors continuously capture data and send it to the control unit.
b) The data includes audio, temperature, movement (from accelerometer and gyroscope), and rumination levels.
c) The raw sensor data is cleaned and normalized.
d) Time-stamping ensures data synchronization across all sensors.
e) Missing or noisy data is handled through interpolation or filtering.
f) MFCC features are extracted from cow vocalizations.
g) Rolling averages, spikes, and fluctuations are analyzed.
h) Activity level features are computed from accelerometer and gyroscope data.
i) Total chewing time and frequency are calculated.
j) The extracted features are fed into a trained machine learning model The model outputs predictions in real-time.
k) These predictions help determine if the cow is ready for insemination or showing signs of distress.
l) Predictions trigger automated alerts.
m) Results are displayed on a user-friendly mobile dashboard showing individual cow statuses.
n) All raw and processed data is stored in the storage unit (5) for future use, audits, or retraining of the model.
3. The IoT based smart system for cattle/ cow’s health and oestrous cycle monitoring, as claimed in claim 1, wherein the audio sensors (1) to detect cow vocalizations (MFCC features help classify cow sounds related to heat periods);