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Edge technology aims to bring Cloud resources (specifically, the compute,storage, and network) to the closed proximity of the Edge devices, i.e., smartdevices where the data are produced and consumed. Embedding computing andapplication in Edge devices lead to emerging of two new concepts in Edgetechnology, namely, Edge computing and Edge analytics. Edge analytics uses sometechniques or algorithms to analyze the data generated by the Edge devices.With the emerging of Edge analytics, the Edge devices have become a completeset. Currently, Edge analytics is unable to provide full support for theexecution of the analytic techniques. The Edge devices cannot execute advancedand sophisticated analytic algorithms following various constraints such aslimited power supply, small memory size, limited resources, etc. This articleaims to provide a detailed discussion on Edge analytics. A clear explanation todistinguish between the three concepts of Edge technology, namely, Edgedevices, Edge computing, and Edge analytics, along with their issues.Furthermore, the article discusses the implementation of Edge analytics tosolve many problems in various areas such as retail, agriculture, industry, andhealthcare. In addition, the research papers of the state-of-the-art edgeanalytics are rigorously reviewed in this article to explore the existingissues, emerging challenges, research opportunities and their directions, andapplications.

A Review on Edge Analytics: Issues, Challenges, Opportunities, Promises, Future Directions, and Applications