information Review Low-Cost Automatic Weather Stations in the Internet of Things Konstantinos Ioannou 1,* , Dimitris Karampatzakis 2 , Petros Amanatidis 2, Vasileios Aggelopoulos 2 and Ilias Karmiris 1 1 Hellenic Agricultural Organization “DEMETER”, Forest Research Institute, Vasilika, 57006 Thessaloniki, Greece;
[email protected] 2 Industrial and Educational Embedded Systems Lab, Department of Computer Science, International Hellenic University, 65403 Kavala, Greece;
[email protected] (D.K.);
[email protected] (P.A.);
[email protected] (V.A.) * Correspondence:
[email protected] Abstract: Automatic Weather Stations (AWS) are extensively used for gathering meteorological and climatic data. The World Meteorological Organization (WMO) provides publications with guidelines for the implementation, installation, and usages of these stations. Nowadays, in the new era of the Internet of Things, there is an ever-increasing necessity for the implementation of automatic observing systems that will provide scientists with the real-time data needed to design and apply proper environmental policy. In this paper, an extended review is performed regarding the technologies currently used for the implementation of Automatic Weather Stations. Furthermore, we also present the usage of new emerging technologies such as the Internet of Things, Edge Computing, Deep Learning, LPWAN, etc. in the implementation of future AWS-based observation systems. Finally, we present a case study and results from a testbed AWS (project AgroComp) developed by our research team. The results include test measurements from low-cost sensors installed on the unit and predictions provided by Deep Learning algorithms running locally. Citation: Ioannou, K.; Keywords: AWS; Internet of Things; Artificial Intelligence; Edge computing; LPWAN; LoRa; AgroComp Karampatzakis, D.; Amanatidis, P.; Aggelopoulos, V.; Karmiris, I.