Athena Security creates various products that help protect against hidden threats. These products include things like elevated temperature detection, people counting sensors and visual gun detection. The client relies on computer vision and other AI technologies to power their products and increase their accuracy and effectiveness.
Due to the ongoing COVID-19 pandemic, companies across industries were looking for specific thermal vision cameras to be used in various public areas. These cameras could be used to check for elevated temperatures and count the number of people within the premises. While there are various solutions on the market already, the demand is very high, and reasonably priced alternative solutions are welcome.
The client was looking to offer its own product to the market with enhanced capabilities, but they needed to develop a middleware solution that would provide connectivity between the application and the hardware while managing the data received from it. Also, all of the needed settings needed to be adjusted as well as the ability to focus on specific frame areas and obtain accurate results from the thermal readings.
The current solution was built on Linux and available on both Linux and Windows OS. While they were able to connect the Camera and provide service with this setup, the market demand was to perform such thermal scanning using the iPad on iOS. This meant that they needed to migrate the application and functionality of the Linux version to iOS to allow for thermal scanning in any selected area of the frame.
Solutions Provided by Team.Harbour
Team.Harbour assembled a team for the client that consisted of one iOS developer and a project manager. We created a solution that allowed the client to:
The solution was also accessible on iOS devices as well.
Thanks to the development work provided by Team.Harbour, the client was able to satisfy market requirements and increase the scope of their service offering. They were able to do all of this while enjoying significant cost savings as well. The client was very pleased by the accuracy on iOS devices and was just as good as on Linux and Windows