Study and analysis of SARIMA and LSTM in forecasting time series data

As the technology is advancing in each and every field, it also advanced in making houses smarter where one can control the appliance remotely. Here the word smart also helps in generating the electricity bill in a way of reducing the human effort in calculating all the necessary parameters. But not every person knows how electricity works and how the bill is generated. So, the main objective of this project is to let every user know how the consumption of each appliance effect the electricity bill. This project also helps the user to control the home appliance remotely using a smart phone. Accordingly, this research work has developed a Smart system for leveraging a controlled and effective billing. Generally, disabled or elderly people find it difficult to near the switch and turn it on/off in a home. So, the application designed in this paper will fulfill the need. Current and Voltage sensors are used to get the values of voltage and current which will be further used in the generation of bill. The values from the sensors are communicated to the Arduino UNO through I/O ports and the bill is generated. Here, a Bluetooth module is used which acts as a medium and helps the data gets transmitted. All the necessary controls of the appliance and its energy consumption will be present in an Android Application.

Arduino based Smart System for Control and Effective Billing

Cost/comfort-oriented clustering-based extended time of use pricing

The demand for electricity power consumption (PC) is growing lots due to the upward thrust of hardware and the development of the population. Hence it is mandatory to predict energy to enhance its management and co-operation among the energy utilized in a construction and the power grid. There is a problem for predicting the Energy Consumption Prediction (ECP) due to tremendous problems like climate conditions and the effective behaviour of tenants. We present a keen crossover approach that joins Convolutional Neural Network (CNN) with Gated Recurrent Unit (GRU) method which is a Deep Learning technique through three steps which achieves better prediction results when compared to other existing techniques.

Household Electricity Power Consumption Prediction Using CNN-GRU Techniques

The market monitoring system is regarded as an essential technique to check the high pricing, bad quality, and measurement issues of any selling products or items. Currently, available research works/systems are mainly focused on offline-based market monitoring solutions. The offline-based solution is suffered from manpower and irregularity issues, thus experiencing a very low success rate in terms of market monitoring problem-solving. The available literary works did not provide any online-based market monitoring solution with the best shop selection, high pricing issues and product information checking, police reporting, and adding reviews/rating features. To encounter the existing challenges, this paper brings a smart mobile application featuring market product information and seller profit checking by investigating the QR codes and retailers’ asking prices. This paper contributes to the best shop selection for purchasing products by evaluating product names, costs, locations, and ratings. The proposed market spy mobile application provides features like online marketing, reporting against the seller, adding reviews, and rating for the seller shop. The evaluation/review results with up to 70% positive acceptance remarks declare the superiority of the proposed application over the existing schemes. 

Market Spy: A Smart Mobile Application Featuring Market Price, Seller Reporting, and Product Monitoring System for the Bangladeshi Citizen

In Smart Grid, the Smart meters assume different role with smart capacities so as to satisfy the consumer’s needs. The Smart meter can gauge and impart detailed real time power utilization, empower remote continuous checking and control utilizations. The consumers are given ongoing valuing and analyses devoured data, with its technical information which is transmitted from the network, and furthermore give progressively itemized input on every machine to the consumer. This paper gives a review of the prediction and monitoring with respect to control utilization. It is focused to real time scenario like Smart metering and home apparatus like home sight and sound substance over the power utilization grid.

P Maragathavalli

Papers

Smart Electricity meter on Real time Price Forecasting and Monitoring system