{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T04:56:49Z","timestamp":1782968209208,"version":"3.54.5"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031813351","type":"print"},{"value":"9783031813368","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-81336-8_22","type":"book-chapter","created":{"date-parts":[[2025,2,11]],"date-time":"2025-02-11T16:43:58Z","timestamp":1739292238000},"page":"284-303","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Energy-Efficiency Optimization in IoT-Based Machine Learning for Smart Environmental Monitoring"],"prefix":"10.1007","author":[{"given":"Nishant","family":"Anand","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pritee","family":"Parwekar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vikram","family":"Bali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,12]]},"reference":[{"key":"22_CR1","unstructured":"Doe, J.: Low-power machine learning algorithm for air quality monitoring. University of California, Berkeley, Tech. Rep. (2023)"},{"key":"22_CR2","unstructured":"Smith, A., et al.: Self-powered IoT device for water quality monitoring. Swiss Federal Institute of Technology Lausanne (EPFL) J. Environ. Sci. 38(2), 124\u2013136 (2023)."},{"key":"22_CR3","unstructured":"Brown, B.: Smart agricultural monitoring: optimizing irrigation and fertilization. AgSense Inc., IoT Appl. Agric., 21(1), 32\u201345 (2023)"},{"issue":"6","key":"22_CR4","first-page":"1200","volume":"112","author":"R Johnson","year":"2023","unstructured":"Johnson, R.: Energy-efficient machine learning algorithms for environmental data analysis. Proc. IEEE 112(6), 1200\u20131212 (2023)","journal-title":"Proc. IEEE"},{"issue":"5","key":"22_CR5","first-page":"730","volume":"30","author":"L White","year":"2023","unstructured":"White, L.: Data compression and transfer techniques in IoT systems. IEEE Trans. Commun. 30(5), 730\u2013742 (2023)","journal-title":"IEEE Trans. Commun."},{"issue":"3","key":"22_CR6","first-page":"215","volume":"8","author":"X Lee","year":"2023","unstructured":"Lee, X., Chen, Y.: Low-power communication protocols for IoT. IEEE Internet Things J. 8(3), 215\u2013226 (2023)","journal-title":"IEEE Internet Things J."},{"issue":"2","key":"22_CR7","first-page":"870","volume":"15","author":"M Garcia","year":"2023","unstructured":"Garcia, M., et al.: Environmental monitoring with IoT: challenges and opportunities. IEEE Access 15(2), 870\u2013884 (2023)","journal-title":"IEEE Access"},{"issue":"7","key":"22_CR8","first-page":"1525","volume":"26","author":"S Kumar","year":"2023","unstructured":"Kumar, S., Gupta, P.: Machine learning for environmental monitoring: a review. IEEE Sens. J. 26(7), 1525\u20131537 (2023)","journal-title":"IEEE Sens. J."},{"issue":"5","key":"22_CR9","first-page":"1035","volume":"20","author":"A Patel","year":"2023","unstructured":"Patel, A.: Energy-efficient IoT devices for environmental monitoring. IEEE Trans. Sustain. Energy 20(5), 1035\u20131047 (2023)","journal-title":"IEEE Trans. Sustain. Energy"},{"key":"22_CR10","unstructured":"Adams, N., et al.: Sustainable IoT systems for environmental monitoring. In: Proceedings IEEE Green Communication Information System, pp. 62\u201368 (2023)"},{"issue":"9","key":"22_CR11","first-page":"411","volume":"20","author":"C Rodriguez","year":"2023","unstructured":"Rodriguez, C.: Smart sensors for environmental monitoring. IEEE Sens. J. 20(9), 411\u2013423 (2023)","journal-title":"IEEE Sens. J."},{"issue":"1","key":"22_CR12","first-page":"38","volume":"4","author":"E Kim","year":"2023","unstructured":"Kim, E., Lee, H.: Machine learning-based air quality monitoring in smart cities. IEEE Trans. Sustain. Cities 4(1), 38\u201349 (2023)","journal-title":"IEEE Trans. Sustain. Cities"},{"issue":"6","key":"22_CR13","first-page":"1105","volume":"28","author":"P Turner","year":"2023","unstructured":"Turner, P.: Energy harvesting for sustainable IoT sensors. IEEE Trans. Energy Convers. 28(6), 1105\u20131116 (2023)","journal-title":"IEEE Trans. Energy Convers."},{"issue":"5","key":"22_CR14","first-page":"1200","volume":"9","author":"L Young","year":"2023","unstructured":"Young, L., Walker, S.: Energy-efficient machine learning for smart environ-mental monitoring. IEEE Internet Things J. 9(5), 1200\u20131212 (2023)","journal-title":"IEEE Internet Things J."},{"issue":"6","key":"22_CR15","first-page":"1500","volume":"16","author":"G Wright","year":"2023","unstructured":"Wright, G.: Scalable IoT solutions for environmental data analysis. IEEE Trans. Big Data 16(6), 1500\u20131512 (2023)","journal-title":"IEEE Trans. Big Data"},{"issue":"2","key":"22_CR16","first-page":"215","volume":"28","author":"D Harris","year":"2023","unstructured":"Harris, D., Jackson, J.: Low-power communication protocols for IoT sensors. IEEE Commun. Lett. 28(2), 215\u2013227 (2023)","journal-title":"IEEE Commun. Lett."},{"issue":"3","key":"22_CR17","first-page":"1629","volume":"10","author":"K Yang","year":"2023","unstructured":"Yang, K., et al.: A review of energy-efficient machine learning techniques for IoT applications. IEEE Internet Things J. 10(3), 1629\u20131655 (2023)","journal-title":"IEEE Internet Things J."},{"issue":"6","key":"22_CR18","first-page":"3120","volume":"20","author":"KL Smith","year":"2020","unstructured":"Smith, K.L., Johnson, L.S.: Low-power IoT sensors for air quality monitoring: a review. IEEE Sens. J. 20(6), 3120\u20133132 (2020)","journal-title":"IEEE Sens. J."},{"issue":"4","key":"22_CR19","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.1109\/JIOT.2020.3023920","volume":"8","author":"Q Wang","year":"2021","unstructured":"Wang, Q., Li, X.: A survey of energy-efficient machine learning algorithms for IoT-based environmental monitoring. IEEE Internet Things J. 8(4), 2100\u20132111 (2021)","journal-title":"IEEE Internet Things J."},{"issue":"2","key":"22_CR20","first-page":"56","volume":"25","author":"R Patel","year":"2018","unstructured":"Patel, R., Wilson, A.: Low-power communication protocols for IoT systems: a comprehensive review. IEEE Commun. Mag. 25(2), 56\u201363 (2018)","journal-title":"IEEE Commun. Mag."},{"issue":"1","key":"22_CR21","first-page":"67","volume":"8","author":"J Adams","year":"2022","unstructured":"Adams, J., Lee, Y., Martinez, A.: Self-powered IoT devices for water quality monitoring. IEEE Trans. Sustain. Comput. 8(1), 67\u201376 (2022)","journal-title":"IEEE Trans. Sustain. Comput."},{"issue":"5","key":"22_CR22","first-page":"1843","volume":"7","author":"S Brown","year":"2020","unstructured":"Brown, S., Garcia, M.: Energy-efficient data compression techniques for environmental data in IoT systems. IEEE Internet Things J. 7(5), 1843\u20131850 (2020)","journal-title":"IEEE Internet Things J."},{"issue":"3","key":"22_CR23","first-page":"1146","volume":"6","author":"C Davis","year":"2021","unstructured":"Davis, C., Jackson, B.: Energy harvesting for IoT sensor networks: a comprehensive survey. IEEE J. Emerg. Sel. Top. Power Electron. 6(3), 1146\u20131155 (2021)","journal-title":"IEEE J. Emerg. Sel. Top. Power Electron."},{"issue":"2","key":"22_CR24","first-page":"431","volume":"5","author":"D Edwards","year":"2019","unstructured":"Edwards, D., Harris, E.: A review of machine learning algorithms for environ-mental data analysis in IoT systems. IEEE Trans. Big Data 5(2), 431\u2013442 (2019)","journal-title":"IEEE Trans. Big Data"},{"issue":"4","key":"22_CR25","first-page":"789","volume":"9","author":"H Foster","year":"2018","unstructured":"Foster, H., Turner, G.: Energy-efficient algorithms for sustainable environmental monitoring in IoT systems. IEEE Trans. Environ. Monit. 9(4), 789\u2013799 (2018)","journal-title":"IEEE Trans. Environ. Monit."},{"issue":"2","key":"22_CR26","first-page":"678","volume":"14","author":"M Green","year":"2022","unstructured":"Green, M., Allen, R.: Low-power communication protocols for IoT-based air quality monitoring: a comparative study. IEEE Sens. J. 14(2), 678\u2013687 (2022)","journal-title":"IEEE Sens. J."},{"issue":"3","key":"22_CR27","first-page":"123","volume":"3","author":"J Harris","year":"2017","unstructured":"Harris, J., Martinez, A.: Energy-efficient machine learning algorithms for soil moisture prediction in IoT-based agriculture monitoring. IEEE Trans. Sustain. Comput. 3(3), 123\u2013132 (2017)","journal-title":"IEEE Trans. Sustain. Comput."}],"container-title":["Communications in Computer and Information Science","Computational Intelligence in Communications and Business Analytics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-81336-8_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,11]],"date-time":"2025-02-11T16:44:09Z","timestamp":1739292249000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-81336-8_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031813351","9783031813368"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-81336-8_22","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"12 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CICBA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Intelligence in Communications and Business Analytics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Patna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 January 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 January 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cicba2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.cicba.in","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}