For several months, we tried building and collecting temperature sensor data from a number of devices and sensors, but we had the most success with ultra low-power microcontrollers. This was because we needed to develop a system that could run on solar power for extended periods of time.

We programmed all of the integrated applications on Python, Micropython, and Swift. This was critical for optimizing the code to run efficiently on our solar-powered devices.

We architected the application to collect, validate, log, and report temperature data in real time, providing the most up-to-date information possible. We built the application on an cloud environment, and we are actively working to establish a long-term cloud partner for mass collection of data starting in 2025.

Once we deploy over 25 temperature sensors in California, we will start analyzing the data and using artificial intelligence to generate predicted walking dog times. To ensure accuracy, we will take additional factors into consideration, such as humidity, altitude, and wind speed.

Our main goal is to provide accurate and timely information to help pet owners keep their dogs safe on hot days. We believe that our system has the potential to make a real difference in the lives of dogs and their owners.