Paper Name

Summary

Contribution

Objectives

Methodology

Data collection tool

Outcomes

Gaps

1

A novel smart energy theft system (SETS) for IoT-based smart home.

Smart home networks are vulnerable to energy theft. Certain devices have to be installed to detect the attacks. An energy detection system that is based on statistical models and machine learning can be developed.

Developing an energy theft detection system to enhance the security of smart homes.

To propose a novel idea of Smart Energy Theft Systems for the smart home

The researchers reviewed the existing literature to determine how to reduce energy thefts. There was simulation of the smart energy theft system.

Literature review

An innovative smart energy theft system was developed for energy theft detection

The efficiency and effectiveness of the smart energy theft systems

2

Theft detection system using PIR sensor.

The implementation of a smart surveillance system by use of PIR and PR sensor can help improve home security. PIR detects the motion of objects. The PIR sensor is integrated with the camera to ensure that if there are movements in the room, the camera switches on. There is a mail system for providing the owner with a live stream of motion in the house. The smart home automation system can be used for theft detection

Developing a smart home automation system that can be used for theft detection

To implement a smart surveillance system by use of PIR and PR sensor for theft detection

Literature survey to determine how PIR sensors work and how they can be implemented. There was software implementation by use of Python and PR programming language

Literature review

Design of a smart surveillance system that can capture images and videos and send to a mobile phone

Information about limitations of the PIR sensors

3

Internet of Things Enabled Power Theft Detection and Smart Meter Monitoring System.

Power theft is an issue that concerns distribution companies. Smart meters with ICT can be used for detecting and alerting power theft. Internet of Things can be used in smart meter monitoring and power theft detection

Development of a system that detects power theft due to direct line hooking, meter tampering and meter bypass.

To reduce power theft in distribution companies

To develop an IoT enabled power theft detection system

The IoT enabled smart meter was designed with tampering detection circuit. An IoT server was developed by use of publish subscribe architecture, and an android application was designed by use of android studio 2.3

Online records

Prevention of theft by implementing an IoT enabled power theft detection system and smart meter monitoring system

How the linear-based approach detects power theft

4

Intrusion detection for cybersecurity of smart meters. 

The use of information communications technology enables real-time communication for smart meters. The infrastructures are; however, vulnerable to cyber-attacks. A two-stage cyber intrusion protection system is proposed for smart meters.

Proposal of a two-stage cyber intrusion protection system for smart meters.

To develop a system for protecting smart meters from cyber attacks

The researcher conducted research and proposed detection algorithms for detecting abnormal behaviours in smart meters. The support vector machine detection technique was used for analysing associated data for solving classification problems

Internet

Solving the cyber security vulnerabilities of smart meters

Effectiveness of the intrusion detection systems for smart meters.

5

Electricity theft detection in smart grid systems.

Electricity theft has severe consequences for the providers. Smart grids reduce the losses by using data analysis technique. Deep learning technique and machine learning can be used for identifying theft users.

Proposing an electricity theft detection system based on convolutional neural network (CNN) and long short-term memory (LSTM) architecture

To identity ways of reducing electricity theft

Electricity theft data was collected from a website. There was data pre-processing, training and testing of data. The proposed model was hyper tuned and the optimized model was evaluated.

Documents and records

Reduction of electricity theft in smart grid systems

Inefficiency of the model in identifying electricity theft users

6

Electricity theft detection using supervised learning techniques on smart meter data. 

The number of electricity thieves has been increasing. There is need to conduct research to detect electricity thieves accurately. A model based on real electricity data and machine learning technique can be developed to detect the electricity thieves.

Identification of electricity thieves using smart meter data.

To develop an electricity theft detection system on smart meters.

There was collection of electricity data. A proposed system model was developed. It included data pre-processing, data balancing, feature extraction, classification and validation. Simulations were conducted to show the performance of the models.

Online documents and records

Significant reduction in the number of electricity thieves

How utility companies can apply the models to identify electricity thieves