An IoT based Green Home Architecture for Green Score Calculation towards Smart Sustainable Cities

Abstract

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

Coral Reef Optimization for Predicting Features in Multiobjective Clustering Bio-Inspired Dataset

“…Given a dataset, significant segment age systems are utilized to convey different gathered urgent groups. Sporadic Part Assurance, on the other hand, uses the standard bunching method to bunch fragmented data, while Unpredictable Limit Assurance uses grouping procedures with moved limits [7,8].…”

DeepQ Based Heterogeneous Clustering Hybrid Cloud Prediction Using K-Means Algorithm

“…There are not many fundamental periods of current DDM techniques: 1) restricted experiments with local data on various websites; and 2) the production of prototypes on a national scale by aggregating local results. Because naive direct detection techniques would produce international data models that are unreliable and uncertain, these additional parallel steps are not autonomous [5]. Therefore, DDM would provide an environmental perspective that not only minimizes the impact of local consequences on existing models but also encourages their adoption in order to take advantage of the benefits of collecting information at multiple locations.…”