Guest Editorial:Special issue on explainable AI empowered for indoor positioning and indoor navigation  

作　　者：Ki‐Il Kim Aswani Kumar Cherukuri Xue Jun Li Tanveer Ahmad Muhammad Rafiq Shehzad Ashraf Chaudhry 

机构地区：[1]Chungnam National University,Daejeon,Republic of Korea [2]Vellore Institute of Technology,Vellore,India [3]Auckland University of Technology,Auckland,New Zealand [4]Yeungnam University,Gyeongsan‐si,Republic of Korea [5]Abu Dhabi University,Zayed City,UAE

出　　处：《CAAI Transactions on Intelligence Technology》2023年第4期1101-1103,共3页智能技术学报（英文）

摘　　要：The convergence of Internet of Things(IoT),vehicularad hoc network(VANET),and mobile ad hoc network relies on sensor networks to gather data from nodes or objects.These networks involve nodes,gateways,and anchors,operating on limited battery power,mainly used in broadcasting.IoT applications,like healthcare,smart cities,and transportation,often need position data and face challenges in delay sensitivity.Localisation is important in ITS and VANETs,influencing autonomous vehicles,collision warning systems,and road information dissemination.A robust localisation system,often combining GPS with techniques like Dead Reckoning and Image/Video Localisation,is essential for accuracy and security.Artificial intelligence(AI)integration,particularly in machine learning,enhances indoor wireless localisation effectiveness.Advancements in wireless communication(WSN,IoT,and massive MIMO)transform dense environments into programmable entities,but pose challenges in aligning self‐learning AI with sensor tech for accuracy and budget considerations.We seek original research on sensor localisation,fusion,protocols,and positioning algorithms,inviting contributions from industry and academia to address these evolving challenges.

关 键 词：ANCHOR artificial intelligence GPS LOCALISATION mobile communication RSSI VEHICLE 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]