Smart Buildings

This project uses the versatile Particle M-SoM that offeres reliable connectivity using both WiFi and cellular networks to create a flexible proof of concept for a parking management system.

This project utilizes Arduino Nicla Sense ME and Nicla Sens Vision systems to monitor and analyze environmental conditions, occupancy, air quality, temperature, humidity and other factors. Data can be used to assess the air quality in the office building.

This project uses the versatile Particle M-SoM that offeres reliable connectivity using both WiFi and cellular networks to create a resilient proof of concept for an access management solution of smart buildings.

This project focuses on developing cutting-edge voice commands for smart home appliances. The challenge lies in natural language recognition, keyword detection and fine-tuning of voice recognition algorithms. To increase security and maintain privacy, we are proposing an edge-running IoT device with a machine learning algorithm that will not store any data during detection.

This project involves using the Gigadevice processor, sensors, and an Edge Impulse model to create a custom gas tracker. Gas sensors can be used to detect leaks in confined spaces, reduce environmental pollution, improve energy efficiency, monitor engine performance and minimize emissions. This technology can help reduce the exposure time of employees to various hazardous agents.

Building Management Systems use sensor data to control lights, temperature, and ventilation, saving energy and optimizing usage. Sensors are used in conjunction with machine learning algorithms to detect human presence.