Node Detection and Tracking in Smart Cities Based on Internet of Things and Machine Learning

Authors

DOI:

https://doi.org/10.21928/uhdjst.v3n1y2019.pp30-38

Keywords:

Detection, Global Positioning System, Internet of Things, K-Nearest Neighbors, Location, Node Tracking, Radiofrequency Identification

Abstract

It is essential to know that using technologies in a good manner will facilitate human live. Internet of Things (IoT) used widely due to developments in information and verbal exchange technologies. Some of the most famous fields of IoT applications are Identification, transmission, and healthcare which uses IoT technologies to collect information and recognizing the problem and propose the solution for it. In this paper, we try to find RFID nodes and their location. An Android Application used to provide help for those needed. Finding and detection the actual zone of our users are done by using KNN algorithm. We use 3NN because that model gets a better result in our dataset, for transmission depending on the users’ problem.

We use a new equation to find weights that integrated with Dijkstra's algorithm, the equation is to calculate the weight between any two nodes using traffic information and image processing for finding a load of road by counting number of vehicles inside the image that collected from our readers. Dijkstra's algorithm is used to find the best path between source and destination using weights between nodes. The idea is used in healthcare, but can be used in many other fields like, security, Information and Communication Technology and Military.

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Published

2019-05-26

How to Cite

Teimoor, R. A., & Darwesh, A. M. (2019). Node Detection and Tracking in Smart Cities Based on Internet of Things and Machine Learning. UHD Journal of Science and Technology, 3(1), 30–38. https://doi.org/10.21928/uhdjst.v3n1y2019.pp30-38

Issue

Section

Articles