Design and Implementation of a Smart Energy Meter Based on Internet of Things and Neural Network Approach

Priya, Srishti; Srivastava, Archit; Jindal, Sumit Kumar; Sahoo, Sarat Kumar

doi:10.2139/ssrn.3170196

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…What sets this design apart from the others is the use of Neural Network Time Series in MATLAB. In addition to being inexpensive, this system has characteristics like online payment, quick real-time settlement and error detection, the removal of human intervention, and the ability to easily watch the entire process from a distance [7]. Somewhere else, writers attempted to design a device that would be able to measure and report energy use over a network.…”

Section: Literature Surveymentioning

confidence: 99%

Iot-Based Smart Energy Meter Reading and Billing System

Tripathi,

Maurya,

Kumar

et al. 2024

International Journal of Innovative Research in Computer Science and Technology (IJIRCST)

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There has been rapid progress towards the development of smart cities in the recent past. A smart city is an urban area that uses advanced technology for efficient monitoring and managing of resources- with an aim of improving the quality of life of its residents, and also optimizing the cost and energy requirements. Focusing on energy related monitoring, the basic component which serves as the foundation for all data collection, analysis and automation is a smart energy meter. This paper takes a conventional energy meter and with few modifications like Arduino and GSM module added to it convert it into a smart energy meter. This smart energy meter is further enhanced with the use of Internet-of-Things (IoT). In order to transmit data over a GSM mobile network, such as consumed energy in kWh, generated bills, etc., the smart energy meter system will integrate an embedded controller (Arduino) with a GSM modem. The data collected from the user end can be provided to the Energy providers or Power companies, enabling them to monitor and control the services for their customers without the need for human labour can be achieved using IoT. Also integrating the smart meter with IOT, the user can access the data from anywhere in the world using an Id and Password provided to them. Our project will be helpful for major energy corporations to cut down extra labour cost and minimize the error and losses while also being User friendly.

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Section: Literature Surveymentioning

confidence: 99%

Iot-Based Smart Energy Meter Reading and Billing System

Tripathi,

Maurya,

Kumar

et al. 2024

International Journal of Innovative Research in Computer Science and Technology (IJIRCST)

View full text Add to dashboard Cite

show abstract

“…Any kind of equipment can be used, including household appliances, automobiles, industrial machinery, electronic gadgets, and any machine or sensor that is connected to a network. The primary goal of the Internet of Things is to link devices to one another over a network and utilize those devices to gather and distribute data, which enhances productivity, performance, automation, and the system's ability to make decisions [7]. Systems may now remotely operate and transfer data to various areas of connected devices via a network thanks to the Internet of Things.…”

Section: Development Using Iotmentioning

confidence: 99%

Advanced Energy Metering System Using IOT

Tripathi,

Maurya,

Kumar

et al. 2024

IJIRCST

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In recent times, there has been a swift advancement in the creation of smart cities. A smart city is a metropolitan area that makes use of cutting-edge technology for effective resource management and monitoring. The goal is to maximize energy and cost savings while simultaneously enhancing the quality of life for its citizens. With an emphasis on energy-related monitoring, a smart energy meter is the fundamental element that forms the basis for all data gathering, analysis, and automation. This paper describes how to turn a regular energy meter into a smart energy meter by adding an Arduino and a GSM module. With the help of the Internet of Things, this smart energy meter is further improved using IoT. An embedded controller (Arduino) and a GSM modem will be integrated by the smart energy meter system to transfer data over a GSM mobile network, such as generated invoices, spent energy in kWh, etc. IoT can be used to enable energy providers and power companies to monitor and control their customers' services without the need for human labour by providing them with the user -generated data. By connecting the smart meter to the Internet of Things, the user can access the data using a password and ID that has been issued from any location in the globe. Major energy companies will benefit from our project's user-friendliness, reduced labour costs, and decreased error and loss rates.

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“…This approach provides very high accuracy of 99.96%; and it ensures the security of IoT based smart home systems. Similarly, neural networks were also applied in the approach for smart energy meter, where the role of neural networks is to analyze the trend of energy consumption in the household [104].…”

Section: Theft Resistancementioning

confidence: 99%

Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review

Ali,

Khan,

Khalid

2023

J Big Data

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Internet of Things (IoT) driven systems have been sharply growing in the recent times but this evolution is hampered by cybersecurity threats like spoofing, denial of service (DoS), distributed denial of service (DDoS) attacks, intrusions, malwares, authentication problems or other fatal attacks. The impacts of these security threats can be diminished by providing protection towards the different IoT security features. Different technological solutions have been presented to cope with the vulnerabilities and providing overall security towards IoT systems operating in numerous environments. In order to attain the full-pledged security of any IoT-driven system the significant contribution presented by artificial neural networks (ANNs) is worthy to be highlighted. Therefore, a systematic approach is presented to unfold the efforts and approaches of ANNs towards the security challenges of IoT. This systematic literature review (SLR) is composed of three (3) research questions (RQs) such that in RQ1, the major focus is to identify security requirements or criteria that defines a full-pledge IoT system. This question also focusses on pinpointing the different types of ANNs approaches that are contributing towards IoT security. In RQ2, we highlighted and discussed the contributions of ANNs approaches for individual security requirement/feature in comprehensive and detailed fashion. In this question, we also determined the various models, frameworks, techniques and algorithms suggested by ANNs for the security advancements of IoT. In RQ3, different security mechanisms presented by ANNs especially towards intrusion detection system (IDS) in IoT along with their performances are comparatively discussed. In this research, 143 research papers have been used for analysis which are providing security solutions towards IoT security issues. A comprehensive and in-depth analysis of selected studies have been made to understand the current research gaps and future research works in this domain.

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Design and Implementation of a Smart Energy Meter Based on Internet of Things and Neural Network Approach

Cited by 6 publications

References 5 publications

Iot-Based Smart Energy Meter Reading and Billing System

Iot-Based Smart Energy Meter Reading and Billing System

Advanced Energy Metering System Using IOT

Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review

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