{"title":"Deterministic Target-Barrier Coverage With Importance-Aware Sensor Deployment in IIoT","authors":"Chien-Fu Cheng;Wen-Hao Lin","doi":"10.1109/JSEN.2025.3598798","DOIUrl":null,"url":null,"abstract":"This study addresses the target-barrier coverage problem in a deterministic deployment setting, considering targets with varying levels of importance. Taking the surveillance of oil exploitation infrastructure in the Industrial Internet of Things (IIoT) as an example, different oil-related facilities within the exploitation area may have distinct levels of importance. To prevent potential damage, target-barriers must be constructed around these infrastructures. Targets of higher importance require target-barriers with extended response times, necessitating distance constraints that vary according to importance levels. To the best of our knowledge, this is the first work to address the target-barrier coverage problem while incorporating different levels of target importance. The primary objective is to minimize the number of deployed sensors needed to construct target-barriers in a deterministic manner while ensuring coverage requirements based on target importance. The minimum number of sensors required for target-barrier construction is analytically determined and formally proven. Additionally, the problem is shown to be NP-hard. Finally, simulation results are presented to evaluate the performance of the proposed algorithm.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 19","pages":"37370-37382"},"PeriodicalIF":4.3000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/11134679/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This study addresses the target-barrier coverage problem in a deterministic deployment setting, considering targets with varying levels of importance. Taking the surveillance of oil exploitation infrastructure in the Industrial Internet of Things (IIoT) as an example, different oil-related facilities within the exploitation area may have distinct levels of importance. To prevent potential damage, target-barriers must be constructed around these infrastructures. Targets of higher importance require target-barriers with extended response times, necessitating distance constraints that vary according to importance levels. To the best of our knowledge, this is the first work to address the target-barrier coverage problem while incorporating different levels of target importance. The primary objective is to minimize the number of deployed sensors needed to construct target-barriers in a deterministic manner while ensuring coverage requirements based on target importance. The minimum number of sensors required for target-barrier construction is analytically determined and formally proven. Additionally, the problem is shown to be NP-hard. Finally, simulation results are presented to evaluate the performance of the proposed algorithm.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice