Publication:
Internet of Things-based Home Automation with Network Mapper and MQTT Protocol

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dc.citedby0
dc.contributor.authorAlam T.en_US
dc.contributor.authorRokonuzzaman M.en_US
dc.contributor.authorSarker S.en_US
dc.contributor.authorAbadin A.F.M.Z.en_US
dc.contributor.authorDebnath T.en_US
dc.contributor.authorHossain M.I.en_US
dc.contributor.authorid58394481900en_US
dc.contributor.authorid57190566039en_US
dc.contributor.authorid57204514782en_US
dc.contributor.authorid59394343100en_US
dc.contributor.authorid59394703200en_US
dc.contributor.authorid57684603000en_US
dc.date.accessioned2025-03-03T07:41:21Z
dc.date.available2025-03-03T07:41:21Z
dc.date.issued2024
dc.description.abstractThe increasing ability of internet-connected daily life electronic gadgets has propelled smart homes into a global trend. The Internet of Things (IoT) enables ambient devices to communicate and interact seamlessly through various sensors. Emerging technical concepts like Web3 and Industry 5.0 require decentralised and intelligent systems near the network's edge. Petabytes of IoT sensor-generated data cause a shortage of storage on the Cloud servers, adding a delay factor to the IoT system. Standard cloud-based IoT systems can't fully function in areas with unstable internet. This paper addresses these challenges and proposes a solution to integrate edge computing concepts. The proposed system is developed using a Raspberry Pi 3 Home Server (RHS) driven by the Support Vector Machine (SVM) algorithm. The designed prototype includes a fire and smoke detection system with MQ2 gas, dust, temperature, and flame sensors. The SVM and these sensors form a data fusion module integrating with Network Mapper (NMAP), Message Queuing Telemetry Transport (MQTT) broker, MariaDB SQL server, and InfluxDB time series database. The experiments demonstrate a fundamental edge operation with a latency of 2.45 ms (milliseconds), while NMAP integration ensures data security and device verification for sensor data storage. The synthetic simulations show positive outcomes for the data fusion-based monitoring system, where alerts are promptly triggered as sensor values change, with an overall system latency of approximately 24 ms. The developed system manages home automation, real-time monitoring for fire, smoke, gas leaks, network scans, anomaly detection, appliance usage tracking, and cloud data backup. A multi-level alert system ensures early threat mitigation, with alarms, SMS, notifications, and email alerts to maximize awareness. ? 2024 The Author(s)en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo109807
dc.identifier.doi10.1016/j.compeleceng.2024.109807
dc.identifier.scopus2-s2.0-85208112697
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85208112697&doi=10.1016%2fj.compeleceng.2024.109807&partnerID=40&md5=da9828db18f741235adb4091d47551d9
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36084
dc.identifier.volume120
dc.publisherElsevier Ltden_US
dc.relation.ispartofAll Open Access; Hybrid Gold Open Access
dc.sourceScopus
dc.sourcetitleComputers and Electrical Engineering
dc.subjectAnomaly detection
dc.subjectCloud storage
dc.subjectDistributed database systems
dc.subjectFire alarm systems
dc.subjectNetwork security
dc.subjectSensor data fusion
dc.subjectSmoke detectors
dc.subjectSteganography
dc.subjectTelemetering systems
dc.subjectEdge computing
dc.subjectFire detection
dc.subjectHome automation
dc.subjectInfluxdb
dc.subjectInternet of thing
dc.subjectNetwork mapper
dc.subjectSmart homes
dc.subjectSupport vector machine
dc.subjectSupport vectors machine
dc.subjectEdge computing
dc.titleInternet of Things-based Home Automation with Network Mapper and MQTT Protocolen_US
dc.typeArticleen_US
dspace.entity.typePublication
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