At Laser Graphictronics, our technology combines advanced wearable sensors, wireless data transmission, and intelligent AI algorithms to transform equine health monitoring into a proactive and reliable system.
Core Technology Pillars
Our hardware solutions can be seamlessly integrated into your fleet. From GPS tracking devices and AI-powered dash cameras to asset monitoring systems and driver performance applications, our technology is designed to significantly enhance operational efficiency. Deployment is simple and scalable, enabling you to reduce costs, improve safety, and optimise fleet management with ease.
Wearable Sensing Devices
This prototype module integrates multiple sensing and communication components in a compact wearable design. The device combines PPG sensors, a GPS module, accelerometer, and a microcontroller with wireless transmission, all powered by a rechargeable battery and secured with a durable strap. Built for equine use, the device is lightweight, robust, and easy to attach, enabling continuous monitoring of vital signs and activity in real-world conditions.
Signal Processing & Data Pipeline
Our system transforms raw physiological signals into actionable insights through a robust data pipeline. Signals from the wearable device are first pre-processed to remove noise and artifacts, using advanced filtering techniques. Once cleaned, the data is transmitted wirelessly to a receiver and processed in real time with Python-based algorithms for peak detection and vital sign calculation. The results are then stored securely in the cloud, enabling veterinarians and owners to access reliable health information anytime, anywhere.
The wearable sensor collects physiological signals directly from the horse and transmits them wirelessly for processing. Raw signals are cleaned through advanced filtering and analyzed in real time, providing reliable heart rate data and actionable health insights.
Intelligent Prediction Models
Intelligent Prediction Models
Our intelligent prediction models leverage advanced machine learning algorithms to transform processed physiological data into accurate health forecasts. By analyzing trends in heart rate, respiratory rate, blood pressure, and movement, the models can identify early signs of stress, fatigue, or potential illness. Using regression, decision trees, and neural networks, our system continuously learns hidden patterns from new data, improving its accuracy over time. These predictive insights help veterinarians and owners take proactive measures, ensuring better care and performance for each horse.
Mobile App
The mobile app features a user-friendly interface supporting user login, horse profile management, device configurations (Wi-Fi connection, data collection rate et. al.), working status of key sensor components such as battery and PPG, and real-time signal-noise ratios.
