Developing a Hybrid Approach with Whale Optimization and Deep Convolutional Neural Networks for Enhancing Security in Smart Home Environments’ Sustainability Through IoT Devices DOI Open Access

R Kavitha,

Balamurugan Vaithiyanathan

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11040 - 11040

Published: Dec. 16, 2024

Even while living circumstances and construction techniques have generally improved, occupants of these spaces frequently feel unsatisfied with the sense security they provide, which leads to looking for eventually enacting ever-more-effective safety precautions. The continuous uncertainty that contemporary individuals experience, particularly regard their protection in places like cities, prompted field computing design smart devices attempt reduce threats ultimately strengthen people’s protection. Intelligent apps were developed provide make a residence safe home. proliferation technology homes necessitates implementation rigorous precautions protect users’ personal information avoid illegal access. importance establishing cyber has been recognized by academic business institutions all around globe. Providing reliable computation Internet Things (IoT) is also crucial. A new method enhancing home environments’ sustainability using IoT presented this paper, combining Whale Optimization Algorithm (WOA) Deep Convolutional Neural Networks (DCNNs). WOA-DCNN hybridization seeks enhance measures efficiently identifying averting possible attacks real time. We show how effective proposed approach defending systems from range risks via in-depth testing analysis. By providing potential path protecting surroundings world growing more linked, research advances state art security.

Language: Английский

Contemporary Methods, Models, and Software for Implementation and Optimization of IoT (Internet of Things) Systems: A Review DOI
Yevheniy Khomenko, Sergii Babichev

Lecture notes on data engineering and communications technologies, Journal Year: 2025, Volume and Issue: unknown, P. 134 - 158

Published: Jan. 1, 2025

Language: Английский

Citations

0
IoT-Based Smart Home Automation System: Ensuring Safety for the Elderly DOI

Fahmida Anjum,

Raiyan Gani,

Maherun Nessa Isty

et al.

Published: May 2, 2024

In today's rapidly changing digital world, smart home automation has become increasingly popular. It revolutionized house systems and improved comfort, efficiency, safety, especially for the elderly. For senior citizens, keeping a safe at each level is very important to avoid any type of hazards. this paper, system been developed focusing on affordability safety. Using microcontrollers such as NodeMCU, Arduino UNO, several sensors mobile applications, built ensure safety low cost. The Internet Things (IoT) also introduced in which gives power operate electrical appliances using devices. proposed redefines contemporary living standards by integrating assurance into daily activities boosting comfort security. After installing sensors, testing, connecting through internet, can secured with an affordable budget This worked greatly making safe. provides its services user when they are well away from home. Specially, ensures security sending immediate notifications alerts if inconvenience happens fire gas leakage. By monitoring presence someone come front door, notifies message or email.

Language: Английский

Citations

1
A secured deep learning based smart home automation system DOI Creative Commons

Chitukula Sanjay,

Konda Jahnavi,

Shyam Karanth

et al.

International Journal of Information Technology, Journal Year: 2024, Volume and Issue: 16(8), P. 5239 - 5245

Published: Aug. 29, 2024

Abstract With the expansion of modern technologies and Internet Things (IoT), concept smart homes has gained tremendous popularity with a view to making people’s lives easier by ensuring secured environment. Several home automation systems have been developed report suspicious activities capturing movements residents. However, these are associated challenges such as weak security, lack interoperability integration IoT devices, timely reporting movements, etc. Therefore, given paper proposes novel framework for controlling appliances integrating sensors, microcontrollers, which would in turn monitor send notifications about on resident’s smartphone. The proposed makes use convolutional neural networks (CNNs) motion detection classification based pre-processing images. images related residents captured spy camera installed system. It helps identification outsiders differentiation patterns. performance is compared existing deep learning models used recent studies evaluation metrics accuracy (%), precision recall f-1 measure (%). results show that attains highest ( 98.67% ), thereby surpassing systems.

Language: Английский

Citations

0
Accurate Identification of IoT Devices in the Presence of Wireless Channel Dynamics DOI
Bhagyashri Tushir,

Vikram K. Ramanna,

Yuhong Liu

et al.

Published: Sept. 9, 2024

Language: Английский

Citations

0
Design and simulation of a smart master switch system based on multi-input XOR logic gate DOI Creative Commons

Jimmy Nabende Wanzala,

Michael Robson Atim

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(1)

Published: Nov. 12, 2024

Abstract Mechanical switches have been the conventional way of controlling electrical energy in different systems such as: lighting systems, socket and circuit breakers, especially domestic, hospital, industrial applications. often require physical access to control devices that are connected power sources. The work presented this paper aimed at designing simulating a multi-input based Exclusive-Or master switch system remotely controls using wireless switching mechanisms Global System for Mobile communication Bluetooth. therefore limits interaction use single pole double throw keypad mechanical however included act as fall-back mechanism devices. Within recommended safety measures, design can be streamlined integrated sockets alongside consumer unit.

Language: Английский

Citations

0
Developing a Hybrid Approach with Whale Optimization and Deep Convolutional Neural Networks for Enhancing Security in Smart Home Environments’ Sustainability Through IoT Devices DOI Open Access

R Kavitha,

Balamurugan Vaithiyanathan

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11040 - 11040

Published: Dec. 16, 2024

Even while living circumstances and construction techniques have generally improved, occupants of these spaces frequently feel unsatisfied with the sense security they provide, which leads to looking for eventually enacting ever-more-effective safety precautions. The continuous uncertainty that contemporary individuals experience, particularly regard their protection in places like cities, prompted field computing design smart devices attempt reduce threats ultimately strengthen people’s protection. Intelligent apps were developed provide make a residence safe home. proliferation technology homes necessitates implementation rigorous precautions protect users’ personal information avoid illegal access. importance establishing cyber has been recognized by academic business institutions all around globe. Providing reliable computation Internet Things (IoT) is also crucial. A new method enhancing home environments’ sustainability using IoT presented this paper, combining Whale Optimization Algorithm (WOA) Deep Convolutional Neural Networks (DCNNs). WOA-DCNN hybridization seeks enhance measures efficiently identifying averting possible attacks real time. We show how effective proposed approach defending systems from range risks via in-depth testing analysis. By providing potential path protecting surroundings world growing more linked, research advances state art security.

Language: Английский

Citations

0