Smart Healthcare Innovation
In partnership with a dynamic a startup originating from Imperial College, we aimed to revolutionise AI-driven healthcare with an intelligent heat detection mat. Their goal was to develop a system that could detect early signs of illness by identifying abnormal temperature patterns. Our role was to provide technical expertise to create reliable firmware, an intuitive graphical user interface (GUI), and machine learning models to power the device.
The Challenge
The startup faced several technical challenges in bringing their intelligent heat detection mat to life. They needed a robust firmware solution to ensure reliable data transmission, efficient data saving, and accurate temperature projection. Additionally, the system required a functional GUI for real-time feedback, and machine learning models to analyse temperature data and offer predictive health insights—all while ensuring system accuracy and efficiency.
The solution
We developed a comprehensive solution that integrated advanced firmware and machine learning for real-time temperature analysis. The system leveraged ESP32 microcontrollers for wireless data transmission and C++ firmware for precise sensor control. A robust C-based server with RESTful APIs managed backend processing, while a secure CRUD database handled temperature data storage and retrieval. The solution ensured seamless integration between hardware and software, providing healthcare professionals with real-time access to critical health indicators.
The features
Machine learning techniques were applied to analyse temperature data in real time ,enabling precise detection of subtle changes. This advanced system improved early illness detection by capturing and processing accurate temperature readings with integrated hardware.
We utilised the ESP32 microcontroller to manage wireless communication and real-time data transmission, ensuring fast and reliable connectivity between the heat detection mat and the central server, allowing healthcare professionals immediate access to temperature analytics.
To ensure efficient operation of the hardware components, we developed C++ firmware to precisely control the mat’s sensors and actuators.
Our C-based server handled back-end data processing and storage, integrating RESTful APIs to enable seamless communication between the detection mat, central database, and front-end GUI.
To manage the large volumes of temperature data generated by the heat detection mat, we built a CRUD (Create, Read, Update, Delete) database that securely stored, managed, and retrieved data as needed.
We selected and implemented a full tech stack, including JavaScript for the front-end GUI, offering healthcare providers a user-friendly interface for real-time visualization of temperature data and insights.
The result
Our solution enabled the startup to overcome its technical challenges and deliver a fully integrated system for real-time temperature detection and illness prediction. The seamless data transmission, robust machine learning models, and intuitive GUI empowered healthcare professionals to monitor patient health more effectively, positioning the startup for accelerated growth in the competitive AI healthcare industry.
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