Mold risk detection to predict and act on environments favorable for mold growth
- Type: Air humidity, Temperature
- Application: Indoor climate, Mold detection, Predictive maintenance, PropTech
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IoT use cases: Indoor climate
IoT for indoor climate
Indoor climate optimization has been a tricky subject for many years. Residents or facility users complain about headaches and fatigue from poor air quality, smell, too much heat, and when the proprietor remedies the issues, new conditions have often had the time to appear. With IoT technology, users can monitor conditions in real-time and quickly respond to the collected data, optimizing conditions for involved parties while avoiding unnecessary operational HVAC costs.
IoT solutions for HVAC
Modern IoT technology opens up true indoor climate optimization through real-time monitoring, predetermined scenarios, and AI algorithms. With the aid of open IoT technology, users become highly flexible when choosing devices and systems and setting up scenarios with the HVAC system.
For example, a sensor can register CO2 levels or room temperatures rising above acceptable levels in a series of conference rooms. Instead of manually maximizing the HVAC system for air conditioning when it is time to use the space, users can implement predetermined scenarios to automatically lower the blinds when the sun is too direct, optimize airflow depending on the number of people in the room, and more.
Data Infrastructure Management System (DiMS)
Sensative and Combain are thrilled to announce our strategic collaboration, marking a new era of AI-powered seamless indoor/outdoor geolocation solutions. The partnership will focus on creating a comprehensive solution for seamless indoor/outdoor geolocation that leverages AI algorithms and deep learning techniques.
