@angus wrote:
I have a case that wants to identify a worker’s smartphone mac address in many different working sites. Currently each worker has a RFID card that to be scanned when they arrive at one of the working sites, eventually, we want to identify his presence by detecting his smartphone mac address (no pre-registration of mac address) without RFID card.
When a worker arrives at working site A and scans his RFID card, his RFID card number will be collected, at the same time about 30 mac addresses nearby. These mac addresses include environmental mac addresses (some environmental mac addresses have been filtered already, some may still be collected), some are other workers’ mac addresses, MAY OR MAY NOT include the particular worker’s mac address depends on whether his phone is screen- on or different smartphone’s setting and behavior. Therefore the following data is captured: {“Working site A” | “RFID card number” | [mac addresses…]}
When this worker arrives working site B, the same data will be captured: {“Working site B” | “RFID card number” | [mac addresses…]}, again the mac addresses MAY OR MAY NOT include his smartphone number. However, if the same mac address is captured at different working sites when the same RFID card number presence, it is likely the mac address belongs to this worker/ RFID card holder.
When the worker arrives working site C, same thing happens. It is even more likely if the same mac address captured with the same RFID number at different working sites.
What algorithms should be used to minimize the data collected and identify the right mac address at a quickest time?
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