Platform Uses AI to Optimise Building Space and Reduce Carbon

The sense_ platform monitors how spaces are used in real-time, and produces specific recommendations aimed at saving money, improving health and reducing environmental impact

Spotted: The British architectural design studio spacelab_ has developed a building management platform that aims to provide actionable insights based on various data sets that are monitored in real-time. The sense_ platform’s algorithms translate the data into specific recommendations related to space occupancy, energy consumption, carbon usage and air quality. 

It allows users to set “space goals”, which are continuously monitored to measure their building’s performance. The platform can then let users know how much space they actually need. For example, a building manager may be able to release space based on their lease agreements. It also provides insights on how best to set it up, so they can make continuous iterative adjustments to their space based on real-time occupancy patterns.

In describing the platform to Springwise, Nathan Lonsdale, sense_’s co-founder, said: “It doesn’t just provide the customer with a whole load of complex data — 92 per cent of building data is never used, largely because people just don’t know how to. For data to be useful, it needs human intervention to decode its value and discover its potential. with sense_, that’s where the actionable insights and recommendations come in.”

One key feature promises to reduce a building’s energy consumption by up to 40 per cent. sense_ does this by connecting to the building’s BMS (building management system) software, which controls heating, cooling and ventilation. The platform can then automatically adjust the BMS to increase efficiency and reduce energy usage via machine learning. 

sense_ also includes safety features like its “COVID safe mode”, which tracks occupancy and will flag the user when unsafe levels are reached. Another mode that is in development and will be added later this year monitors air quality in order to optimise indoor CO2 levels.