Apache Pig is a platform that is used to analyze large data sets. It consists of a high-level language to express data analysis programs, along with the infrastructure to evaluate these programs. One of the most significant features of Pig is that its structure is responsive to significant parallelization. Pig operates on the Hadoop platform,...
Radio frequency fingerprinting is a process that identifies the device or signaler from which a radio transmission originated by looking at the properties of its transmission, including specific radio frequencies. Each signal originator has its own specific "fingerprint" based on the location and configuration of its transmitted signals.
Radio frequency fingerprinting and similar methods are often pursued where global positioning systems or GPS from satellites are unable to trace a signal due to various obstacles. Although radio frequency fingerprinting can be useful in these situations, such as indoors, experts note that there’s still a major challenge in getting unique and stable signals that will lead to positive identification of signal origin. RF readers can look at signal strength and frequency and triangulate a location over time, but the idea that signals can move quickly presents a significant challenge in this kind of monitoring setup.
The phenomenon of radio frequency fingerprinting also creates some significant questions around privacy. The use of these kinds of methods has led to the development of radio frequency identification (RFID) tags. As industry experts are looking at the many different uses for these technologies, such as product scanning in retail and tracking for humans or animals through the use of small RFID chips, many are debating whether these technologies should exist in their current forms or be more regulated and include more protections for those being monitored.
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