INTERNET OF THINGS BASED ZIGBEE SNIFFER FOR SMART AND SECURE HOME

Abstract

The aim of this research is to determine the usage of energy or power with high spectrum allocation in ZigBee Protocol with the help of clustering in IoT. This research starts presenting an overview of the broadband network energy sector and the challenges that are facing. It is observed a change on the energy policies promoting the energy efficiency, encouraging an active role of the consumer, instructing them about the importance of the consumer behavior and protecting consumer rights. Electricity is gaining room as energy source; its share will keep increasing constantly in the following decades. The objective behind this energy consumption segmentation is to be able to provide personalized recommendations to each group in order to reduce their energy consumption and the associated costs, fostering energy efficiency measures and improving the consumer engagement. The desired segmentation is obtained by an iterative process, based on computational clusters calculation (using python programming language) and finalized by a post-clustering analysis applying visualization and statistical data mining technique to detect the energy consumption and reallocate them to a more appropriate group. The K-Means clustering technique was tested and compared, giving the best prediction of accuracy 98.46% for all energy load profiles with high spectrum of 100GHz. The solution from the K-Means clustering is the one that better adapts to the segmentation sought, which is used as the base of the post-clustering stage to obtain the final energy consumption segmentation. Most of these methodologies use the absolute values in 100 kWh, as they were more focused on identify the users with higher energy savings potential. In this case, it allows personalizing energy savings recommendations according to the specific characteristics of ZigBee protocol, improving the consumer experience by being able to provide the adequate advice at the appropriate time, facts that increase the effectiveness of the energy efficiency advises’ service for future ZigBee protocol.