Honeycomb : indoor location estimation based on Wi-Fi signal strength




Linder, Michael, M.S.E.

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This paper presents Honeycomb, an indoor location estimation product based on Wi-Fi signal strength. Wireless Local Area Networks are ubiquitous today, and most people carry Wi-Fi capable devices in their pocket. This existing infrastructure can thus be leveraged for purposes of location estimation. Using Wi-Fi signal strength fingerprinting, Honeycomb harnesses existing Wi-Fi infrastructures as a means to track the movements of individuals through an indoor space. Fingerprinting is a method by which Wi-Fi signal strengths are mapped at regular intervals in a bounded space. Once a space is fingerprinted, a given node must simply sample Wi-Fi signal strengths as it moves through the same space and Honeycomb's algorithm will determine the node’s path in an offline manner. Because Honeycomb only requires nodes to passively measure Wi-Fi signal strengths rather than send out its own beacon, it prevents malicious third parties from gaining access to any real time data, and thus maintains the security and privacy of the user. By performing location estimations on the data collected on an independent platform, and not on the device itself, it saves the user from spending the computing power, and thus the device's battery. We believe Honeycomb to be a product unlike any other, which is suitable for deployment in multiple real world scenarios.



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