Nowadays, most people always have a smartphone and/or any other wearable at hand. These devices send different types of bluetooth and wifi signals to detect nearby devices, communicate with each other, etc....
These signals produce a footprint that can be detected by sensors and be useful for different purposes, one of them being to measure and monitor the occupation and movement of people in enclosed spaces. From them we can build a tool that allows us to analyse the needs of people flow control and space usage analysis. This technology can be applied in all kinds of public spaces, as well as in large shopping centres, where the most frequented routes and places can be measured in order to introduce all kinds of marketing techniques to encourage shopping, or even to trigger air purification, filtering or cleaning mechanisms.
At the same time, in recent years, device manufacturers as well as operating systems have invested time in ensuring sufficient privacy by generating connections with random identifiers so that the tracking of a specific person cannot be identified, making it challenging to infer correct occupancy from devices that are continuously changing their identification. Through AI algorithms, the system developed by Digio uses other inherent data from communications to ascertain that it may be the same person and to track their movements.
In addition, the system is accompanied by a blockchain-based logbook that uniquely and unalterably records the events and actions that take place on the platform.
Digio has been awarded an R&D&I project through the Digital Enabling Technologies grants from the Ministry of Economic Affairs and Digital Transformation, for the development of a platform capable of sensing and monitoring these RF footprints for the detection of occupancy and tracking of people flows.
The project "Platform for occupancy monitoring and indoor atmosphere analysis using machine learning processing of acoustic and radio frequency footprint on an IoT platform with blockchain auditing" with file number 2020/0720/00098945 has been co-funded by the European Union. The aim of the project is to develop an IoT platform that makes use of the capabilities of next generation embedded processing units to create an open project focused on occupancy monitoring and noise control in indoor environments based on the radio frequency signals emitted by the devices or gagdets worn by a person. The main technology to be monitored is Bluetooth Low Energy.
