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509 110 Real-time Location Analytics for Smart Cities P. J. Savnik DTU Space, Technical University of Denmark INTRODUCTION In the Smart City context, there is an increasing demand to adapt the city environment to the behavior and consumption of the people living there. With personal electronic devices that are on-line an opportunity to monitor the behavior of thousands of people electronically arises, with the objective to adapt the environment to its users. City resources can be distributed based on the behavior in real-time and the potential in reduced resources is huge. One can imagine trash bins which are only emptied then full or an App showing where the closest available parking spot is. THEORY The continuously increased popularity of personal wireless devices using Wi-Fi, such as phones etc, enables the development of Wi-Fi based localization techniques. A Wi-Fi enabled mobile device frequently sends out a beacon. This beacon can be picked up by a receiver station. The radio wave path-loss is used to calculate the distance from mobile device to a receiver station. Measurements from at least tree receiver stations are used to trilaterate an exact position of the mobile device. The Cookie Order describes conditions for which such a data collection is legal. METHOD A Wi-Fi module is connected to a computer and set in Monitor mode in order to receive all send Wi-Fi beacons (Probe Request Frames). The computer then subtracts information of the MAC address and Received Signal Strength (RSS). The MAC address is then hashed, using a new algorithm that changes every 24 hours. Then the MAC address, the received signal strength and time are send to a central database. The Server gathers measurements from multiple stations in one database and process the data. Figure 1, System overview for real-time location analytics. RESULTS An experimental setup was tested during the DSE Fair 2016 in March at DTU, tracking visitors and staff. The experimental setup tested the proximity based positioning using cheap commercially available hardware. The result of the experiment proved the concept of using Wi-Fi beacons for real-time location analytics. CONCLUSION Using Wi-Fi to provide real-time data for location analytics has proven to be a feasible method. A newly developed algorithm to anonymise collected data satisfying the laws and regulations from the Cookie Order. This could change how we deploy city resources and adapt in real-time. COMMUNICATION FREESTYLE CONCEPT MASTER LEVEL COURSE/PROJECT


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