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Historically, adoption of Internet of Things (IoT) devices, especially in remote areas like where most farms are located, has been fairly poor but as distributed environments raises at the same pace as the number of IoT devices increases and with it the computational power is moving towards the edge in many other areas, it is pushing remote areas to also adopt IoT. As environmental data collected from IoT devices are not always minimally evaluated at the source. It causes, among others, a bandwidth problem once all collected data for any connected sensor are returned “as is”. Another critical component to be investigated is the security as the edge layer provides an exposed target to attackers, especially with advances of networks like the LPWAN, a very popular networking technology that supports a large amount of underground, underwater or even deep inside building devices for an interesting life time. This paper exposes a possible answer for the question: how to aggregate value to the extra-traffic generated by the 50-75% of IoT devices to be deployed by 2020? There are countless applications for Artificial Intelligence these days, including farm applications, and a lot of labelled data that are daily generated by a diverse of sensors could be used for training purposes elsewhere.
Inspec keywords: Internet of Things; sensors; wide area networks; data acquisition; computerised instrumentation
Subjects: Sensing devices and transducers; Computer communications; Computerised instrumentation; Data acquisition equipment and techniques; Data acquisition systems; Other computer networks; Computerised instrumentation