{"doi":"10.1016/j.iotcps.2023.02.004","title":"Edge AI: A survey","abstract":null,"journal":"Internet of Things and Cyber-Physical Systems","year":2023,"id":652882,"datarank":0.9366250350995606,"base_score":6.244166900663736,"endowment":6.244166900663736,"self_citation_contribution":0.9366250350995606,"citation_network_contribution":0.0,"self_endowment_contribution":0.9366250350995606,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":514,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1703350,"name":"Sukhpal Singh Gill","orcid":"0000-0002-3913-0369","position":1,"is_corresponding":false},{"id":1703349,"name":"Raghubir Singh","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Edge AI: A survey","abstract":"Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI refers to the practice of doing AI computations near the users at the network's edge, instead of centralised location like a cloud service provider's data centre. With the latest innovations in AI efficiency, the proliferation of Internet of Things (IoT) devices, and the rise of edge computing, the potential of edge AI has now been unlocked. This study provides a thorough analysis of AI approaches and capabilities as they pertain to edge computing, or Edge AI. Further, a detailed survey of edge computing and its paradigms including transition to Edge AI is presented to explore the background of each variant proposed for implementing Edge Computing. Furthermore, we discussed the Edge AI approach to deploying AI algorithms and models on edge devices, which are typically resource-constrained devices located at the edge of the network. We also presented the technology used in various modern IoT applications, including autonomous vehicles, smart homes, industrial automation, healthcare, and surveillance. Moreover, the discussion of leveraging machine learning algorithms optimized for resource-constrained environments is presented. Finally, important open challenges and potential research directions in the field of edge computing and edge AI have been identified and investigated. We hope that this article will serve as a common goal for a future blueprint that will unite important stakeholders and facilitates to accelerate development in the field of Edge AI.","is_dataset_classified":null,"base_score":6.192362489474872,"endowment":6.192362489474872,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19162232","pmcid":null,"openalex_id":"https://openalex.org/W4322761281","authors":[],"funders":[],"total_grants":0,"fwci":64.5275,"citation_percentile":0.99982525,"influential_citations":0,"citation_trend":[{"year":2023,"count":45},{"year":2024,"count":112},{"year":2025,"count":200},{"year":2026,"count":131}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://ars.els-cdn.com/content/image/1-s2.0-S2667345223000196-ga1_lrg.jpg","host_type":"journal"},{"url":"https://ars.els-cdn.com/content/image/1-s2.0-S2667345223000196-ga1_lrg.jpg","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S2667345223000196?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S2667345223000196?httpAccept=text/plain","host_type":"publisher"},{"url":"https://doi.org/10.1016/j.iotcps.2023.02.004","host_type":"journal"},{"url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/85043","host_type":"repository"},{"url":"https://doaj.org/article/d63dfae0321b4a10a029bd2131fc4238","host_type":"repository"},{"url":"https://qmro.qmul.ac.uk/xmlui/bitstream/123456789/85043/2/Gill%20Edge%20AI%20A%20survey%202023%20Published.pdf","host_type":"repository"}],"fields_of_study":["IoT and Edge/Fog Computing","Context-Aware Activity Recognition Systems","Age of Information Optimization"],"mesh_terms":[],"keywords":["Edge computing","Edge device","Enhanced Data Rates for GSM Evolution","Computer science","Blueprint","Field (mathematics)","Cloud computing","Artificial intelligence","Applications of artificial intelligence","Automation","Data science","Engineering","Operating system"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Industry, innovation and infrastructure"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-10T17:21:35.658270Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}