Imagimob launches gesture recognition and fall detection solutions based on Texas Instruments mmWave radar

Imagimob has announced the launch of two new applications based on Texas Instruments (TI) mmWave radar sensors, a tinyML development platform for fall detection and gesture recognition.

The fall detection algorithm uses a low-cost, low-power radar sensor that can be placed on the wall of a room or appliance to detect if someone falls in the room. The gesture recognition application can recognize 6 different predefined gestures and can be used for human-machine interfaces in automotive and industrial environments.

Fall detection adds value to different appliances and products by adding health monitoring. It can be used in products within nursing homes, factories or private homes.

Gesture recognition enables functionality through contactless interfaces, which traditionally require buttons/surfaces that take up space and physical touch keys to provide input. This can also cause malfunctions due to wear and tear and require cleaning. Instead, one can use compact radar and gesture recognition applications to eliminate the hassle while also being activated from a distance.

These capabilities are made possible by using the Imagimob tinyML platform and the IWR6843 mmWave radar from Texas Instruments (TI). The application aims to provide customers with a leading edge and reduce time to production.

Imagimob AI can be downloaded for free from the Imagimob website, and the two applications are included in the platform as starter projects. Users can get up and running with development and test applications in minutes. TI mmWave evaluation boards for IWR6843 and IWR6843AOP are also available for purchase.

Imagimob AI is a tinyML end-to-end development platform for machine learning on edge devices. It allows developers to go from data collection to deployment on edge devices in minutes. Imagimob AI is used to build production-ready models for a range of use cases, including sound event detection, audio, gesture recognition, human motion, predictive maintenance, material detection, and more.