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Indoor Positioning System

Photo by Natalya Letunova on Unsplash Indoor Position System (IPS) are the systems used to locate people and goods in indoor environments, where the satellite signal of GPS cannot help. Here at Allinit srl mostly we experienced in hardware and firmware for Wi-Fi tag which use RSSI to guess a position. The use of a Received Signal Strength Indicator (RSSI) is a conventional technique, it is also currently the most used in i-Beacon or other beaconing solution. It has the advantage of being easy to implement because almost all hardware radio receivers have a way to measure it, but it has the big disadvantage that its measures are affected by many environmental factors so that the result cannot be as desired. Based on the fact that the Radio signal strength decrease from the source until reaching the receiver, according to a well known logarithmic function, known the source power and measuring the received signal strength, it is possible to calculate the distance from source

Presence Control

Photo by chuttersnap on Unsplash One of solution we studied here at Allinit srl has been a Presence Control system for a public Hospital. There where various problems there, about employees, but we want remark two solved with our solution. One was related to the safety of healthcare operators. Not rarely the relatives of a victim in an accident had an excessive and sometimes violent reaction to a lousy notice given by a healthcare operator, so a fast way to ask for help from security staff could be useful. The other was that sometimes many employees leave the site, at the same time, without notice or coordination, going the others in difficulty. As you probably guess, the most challenging problem to solve, wasn't the tech solution, but persuade the employees that the answer will not affect their privacy negatively. But this is another story and another post.

Knowledge and Autonomous Analytics

Processed data is information. The processed information is knowledge. Processed knowledge is wisdom. — Ankala V. Subbarao As we imagine, from IoT and the participatory sensing to the mobile crowd sensing, the data sources will reach an incredible number of units, shortly. According to a Gartner Report of 2015, in the year 2020, the IoT devices will reach the 50 billion, and according to Cisco forecast, in the same year the 70% of world population will be connected to the internet, it is about 5.4 billion of connected people. It is quite clear the vast resources need to process all that data, a lot of researches are in place to create new criterion to convert this information in knowledge, but will AI process this knowledge for us beginning the Gurus of future? About Autonomous Analytics here I find an interesting article: "The Impact of AI on Analytics: Machine-Generated Intelligence"

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