Intervention of Innovative Technologies for Eradicating Tampering in Digital Forensics: Practicing Intelligent Decision Methodologies

Deleted Journal, Journal Year: 2024, Volume and Issue: 4, P. 53 - 68

Published: June 30, 2024

The Industrial Internet of Things (IIoT) is one the popular technologies Industry 4.0. This technology involves advanced equipment such as sensors, machines, and analytics platforms in industrial settings. utilized has been harnessed to improve efficiency, productivity, safety. IIoT forensics a specialized field digital that deals with investigation devices. In terms forensics, there are several open challenges, including need for more effective data acquisition techniques, better tools techniques analyzing data, research on legal ethical implications forensics. However, increasing use devices systems presenting new security, privacy, These challenges became an incentive inclusion Blockchain (BCT) which considered most famous 4.0 securing transactions. Wherein, BCT offers solution some security integrity, authentication, access control, confidentiality, transparency, scalability, resilience, provenance. Hence, leveraging ambiances where tampering prevalent, counterfeiting become imperative. this light, can be used due its ability construct transparent environment characterized by decentralized immutable event safety accidents or cyber-attacks. Without doubt, environment, selecting utilizing adequate BC application preventing any alteration unless consensus important. Accordingly, matter catalyst paper constructing robust intelligent appraiser model appraising available nominates applications. context implementing blockchain-based forensic scheme within communication architecture, Multi-Criteria Decision Making (MCDM) strong contributor. Wherein these help balance various criteria preferences amongst applications based on. Entropy Additive Ratio Assessment (ARAS) contributing proposed MCDM. As well working under authority Type-2 neturosophic numbers (T2NN) members Neutrosophic uncertainty theory.

Language: Английский

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AIoT-Based Visual Anomaly Detection in Photovoltaic Sequence Data via Sequence Learning

Energies, Journal Year: 2024, Volume and Issue: 17(21), P. 5369 - 5369

Published: Oct. 29, 2024

Anomaly detection is a common analytical task aimed at identifying rare cases that differ from the majority of typical in dataset. In management photovoltaic (PV) power generation systems, it essential for electric companies to effectively detect anomalies PV sequence data, as this helps operators and experts understand interpret within arrays when making response decisions. However, traditional methods rely on manual labor regular data collection are difficult monitor real time, resulting delays fault localization. Traditional machine learning algorithms slow cumbersome processing which affects operational safety plants. paper, we propose visual analytic approach detecting exploring anomalous sequences dataset via learning. We first compare with their reconstructions through an unsupervised anomaly algorithm (Long Short-Term Memory) based AutoEncoders identify anomalies. To further enhance accuracy detection, integrate artificial intelligence things (AIoT) technology strict time synchronization real-time algorithm. This integration ensures multiple sensors synchronized processed time. Then, analyze characteristics comparison different explore potential correlation factors possible causes Case studies authentic enterprise datasets demonstrate effectiveness our method exploration data.

Language: Английский

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IoT-Driven Smart Trolleys and Robots: Transforming Retail with Edge Computing

Irish Interdisciplinary Journal of Science & Research, Journal Year: 2024, Volume and Issue: 08(02), P. 113 - 122

Published: Jan. 1, 2024

Time is an expensive resource in our fast-paced society, and people frequently lose a good deal of it waiting at supermarket shopping mall checkout counters. An automated intelligent cart has been designed for supermarkets to solve the shortcomings current billing systems. This trolley reduces amount time customers spend counter, improving convenience saving time, by scanning products using Atmega 328 controller RFID tags. Customers can better their experience monitoring items overall cost thanks digital document shown on LCD. With electronic bills sent via email thorough purchase information available through shop's website, manages payment procedures, allowing buy things leave store fast. In order manage product customer information, this system needs Arduino board, reader, tag, LCD display, database manager, website. Leveraging Internet Things (IoT) smooth connection with worldwide network, administrator access anywhere.

Language: Английский

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