{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T06:26:06Z","timestamp":1786947966908,"version":"build-2736575974"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032364920","type":"print"},{"value":"9783032364937","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:00:00Z","timestamp":1787011200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:00:00Z","timestamp":1787011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-3-032-36493-7_4","type":"book-chapter","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T06:08:04Z","timestamp":1786946884000},"page":"46-64","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Agent\u2013Native IoT Data Analytics Platforms: a Reference Architecture"],"prefix":"10.1007","author":[{"given":"Jing","family":"Zeng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,18]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep Learning. Nature. 521, 436\u2013444 (2015)","journal-title":"Nature"},{"key":"4_CR2","unstructured":"Vaswani, A., et al.: Attention is all you need. Proc. NeurIPS, 5998\u20136008 (2017)"},{"key":"4_CR3","unstructured":"Brown, T., et al.: Language models are few-shot learners. Proc. NeurIPS, 1877\u20131901 (2020)"},{"key":"4_CR4","unstructured":"Q. Wu, et al., \"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation,\" https:\/\/arxiv.org\/abs\/2308.08155, (2023)."},{"key":"4_CR5","volume-title":"Proceedings of International Conference on Learning Representations","author":"S Hong","year":"2024","unstructured":"Hong, S., et al.: MetaGPT: meta programming for a multi-agent collaborative framework. In: Proceedings of International Conference on Learning Representations (2024)"},{"key":"4_CR6","unstructured":"Anthropic, \"Model Context Protocol Specification,\" (2024). https:\/\/modelcontextprotocol.io"},{"key":"4_CR7","unstructured":"Google, \"Agent-to-Agent Protocol (A2A),\" (2025). https:\/\/a2a-protocol.org"},{"key":"4_CR8","unstructured":"Apache Iceberg, \"Apache Iceberg: An Open Table Format for Huge Analytic Datasets,\" (2025). https:\/\/iceberg.apache.org"},{"issue":"12","key":"4_CR9","doi-asserted-by":"publisher","first-page":"3411","DOI":"10.14778\/3415478.3415560","volume":"13","author":"M Armbrust","year":"2020","unstructured":"Armbrust, M., et al.: Delta Lake: high-performance ACID table storage over cloud object stores. Proc. VLDB Endow. 13(12), 3411\u20133424 (2020)","journal-title":"Proc. VLDB Endow"},{"key":"4_CR10","unstructured":"Apache Hudi, \"Apache Hudi: Stream Processing on a Data Lake,\" 2025. [Online]. Available: https:\/\/hudi.apache.org"},{"key":"4_CR11","unstructured":"Apache Flink, \"Apache Flink: Stateful Computations over Data Streams,\" (2025). https:\/\/flink.apache.org"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Behm, A., et al.: Photon: a fast query engine for Lakehouse systems. In: Proceedings of ACM SIGMOD, pp. 2326\u20132339 (2022)","DOI":"10.1145\/3514221.3526054"},{"key":"4_CR13","unstructured":"Apache Kafka, \"Apache Kafka: A Distributed Streaming Platform,\" (2025). https:\/\/kafka.apache.org"},{"key":"4_CR14","doi-asserted-by":"publisher","unstructured":"Gao, D., et al.: Text-to-SQL empowered by large language models: a benchmark evaluation. Proc. VLDB Endow. 17(5), 1132\u20131145 (2024). https:\/\/doi.org\/10.14778\/3641204.3641221","DOI":"10.14778\/3641204.3641221"},{"key":"4_CR15","volume-title":"Proceedings Neural Information Processing Systems","author":"M Pourreza","year":"2023","unstructured":"Pourreza, M., Rafiei, D.: DIN-SQL: decomposed in-context learning of text-to-SQL with self-correction. In: Proceedings Neural Information Processing Systems (2023)"},{"key":"4_CR16","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.websem.2012.05.003","volume":"17","author":"M Compton","year":"2012","unstructured":"Compton, M., et al.: The SSN ontology of the W3C semantic sensor network incubator group. J. Web Semantics. 17, 25\u201332 (2012)","journal-title":"J. Web Semantics"},{"key":"4_CR17","first-page":"90","volume-title":"Proceedings of IEEE UIC\/ATC\/ScalCom","author":"M Bermudez-Edo","year":"2016","unstructured":"Bermudez-Edo, M., Elsaleh, T., Barnaghi, P., Taylor, K.: IoT-Lite: a lightweight semantic model for the internet of things. In: Proceedings of IEEE UIC\/ATC\/ScalCom, pp. 90\u201397 (2016)"},{"key":"4_CR18","unstructured":"Neo4j, \"Neo4j Graph Database Platform,\" (2025). https:\/\/neo4j.com"},{"key":"4_CR19","unstructured":"DataHub Project, \"DataHub: The Metadata Platform for the Modern Data Stack,\" (2025). https:\/\/datahubproject.io"},{"key":"4_CR20","unstructured":"Apache Atlas, \"Apache Atlas: Data Governance and Metadata Framework for Hadoop,\" 2025. https:\/\/atlas.apache.org"},{"key":"4_CR21","unstructured":"Lewis, P., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. Adv. Neural Inf. Process. Syst. 33, 9459\u20139474 (2020)"},{"key":"4_CR22","doi-asserted-by":"publisher","unstructured":"Dang, Y., Lin, Q., Huang, P.: AIOps: real-world challenges and research innovations. In: 2019 IEEE\/ACM 41st International Conference on Software Engineering: Companion Proceedings, pp. 4\u20135 (2019). https:\/\/doi.org\/10.1109\/ICSE-Companion.2019.00023","DOI":"10.1109\/ICSE-Companion.2019.00023"},{"key":"4_CR23","unstructured":"Great Expectations, \"Great Expectations: Always Know What to Expect From Your Data,\" (2025). https:\/\/greatexpectations.io"},{"key":"4_CR24","first-page":"2614","volume-title":"Proceedings of ACM SIGMOD","author":"J Wang","year":"2021","unstructured":"Wang, J., et al.: Milvus: a purpose-built vector data management system. In: Proceedings of ACM SIGMOD, pp. 2614\u20132627 (2021)"},{"issue":"2","key":"4_CR25","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1145\/3703155","volume":"43","author":"L Huang","year":"2025","unstructured":"Huang, L., et al.: A survey on hallucination in large language models: principles, taxonomy, challenges, and open questions. ACM Trans. Inf. Syst. 43(2), 42 (2025)","journal-title":"ACM Trans. Inf. Syst."}],"container-title":["Lecture Notes in Computer Science","Internet of Things - ICIOT 2026"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-36493-7_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T06:08:07Z","timestamp":1786946887000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-36493-7_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,18]]},"ISBN":["9783032364920","9783032364937"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-36493-7_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,18]]},"assertion":[{"value":"18 August 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIOT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Internet of Things","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kuala Lumpur","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Malaysia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciot2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.servicessociety.org\/iciot","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}