{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T21:15:28Z","timestamp":1762982128188,"version":"3.44.0"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T00:00:00Z","timestamp":1756512000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T00:00:00Z","timestamp":1756512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Marie Sk\u0142odowska Curie Grant","award":["754382"],"award-info":[{"award-number":["754382"]}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["JCLM project SBPLY\/19\/180501\/000024"],"award-info":[{"award-number":["JCLM project SBPLY\/19\/180501\/000024"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Computing"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s00607-025-01537-5","type":"journal-article","created":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T05:17:17Z","timestamp":1756531037000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An optimal sensor configuration method using genetic algorithms for a fault-tolerant energy management for smart buildings"],"prefix":"10.1007","volume":"107","author":[{"given":"J.","family":"Aguilar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M. D.","family":"R-Moreno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,30]]},"reference":[{"issue":"20","key":"1537_CR1","doi-asserted-by":"publisher","first-page":"9036","DOI":"10.1109\/JSEN.2019.2922409","volume":"19","author":"A Verma","year":"2019","unstructured":"Verma A, Prakash S, Srivastava V, Kumar A, Mukhopadhyay S (2019) Sensing, controlling, and IoT infrastructure in smart building: a review. IEEE Sens J 19(20):9036\u20139046","journal-title":"IEEE Sens J"},{"key":"1537_CR2","doi-asserted-by":"crossref","unstructured":"Sembroiz D, Careglio D, Ricciardi S, Fiore U (2019) Planning and operational energy optimization solutions for smart buildings. Inf Sci 476:439\u2013452","DOI":"10.1016\/j.ins.2018.06.003"},{"key":"1537_CR3","doi-asserted-by":"crossref","unstructured":"Akkaya K, Guvenc I, Aygun R, Pala N, Kadri A (2015) IoT-based occupancy monitoring techniques for energy-efficient smart buildings. In: Proc. IEEE wireless communications and networking conference workshops, pp 58\u201363","DOI":"10.1109\/WCNCW.2015.7122529"},{"key":"1537_CR4","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1016\/j.future.2017.09.082","volume":"82","author":"A Plageras","year":"2018","unstructured":"Plageras A, Psannis K, Stergiou C, Wang H, Gupta B (2018) Efficient IoT-based sensor big data collection\u2013processing and analysis in smart buildings. Future Generation Comput Syst 82:349\u2013357","journal-title":"Future Generation Comput Syst"},{"key":"1537_CR5","unstructured":"Huang Q, Mao C (2016) Occupancy estimation in smart building using hybrid CO2\/light wireless sensor network. J Appl Sci Arts 1(2):5"},{"key":"1537_CR6","doi-asserted-by":"publisher","unstructured":"Lasla N, Doudou M, Djenouri D, Ouadjaout A, Zizoua C (2019) Wireless energy efficient occupancy-monitoring system for smart buildings. Pervasive Mob Comput. https:\/\/doi.org\/10.1016\/j.pmcj.2019.101037","DOI":"10.1016\/j.pmcj.2019.101037"},{"issue":"4","key":"1537_CR7","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1109\/TCE.2017.015014","volume":"63","author":"A Al-Ali","year":"2017","unstructured":"Al-Ali A, Zualkernan I, Rashid M, Gupta R, Alikarar M (2017) A smart home energy management system using IoT and big data analytics approach. IEEE Trans Consum Electron 63(4):426\u2013434","journal-title":"IEEE Trans Consum Electron"},{"issue":"1","key":"1537_CR8","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3233\/MGS-190301","volume":"15","author":"A Maatoug","year":"2019","unstructured":"Maatoug A, Belalem G, Mahmoudi S (2019) Fog computing framework for location-based energy management in smart buildings. Multiagent Grid Syst 15(1):39\u201356","journal-title":"Multiagent Grid Syst"},{"key":"1537_CR9","doi-asserted-by":"publisher","unstructured":"Tushar W, Yuen C, Li K, Wood K, Wei Z, Xiang L (2016) Design of Cloud-Connected IoT system for smart buildings on energy management. EAI Endorsed Trans Ind Networks Intell Syst. https:\/\/doi.org\/10.4108\/eai.1-1-2016.150813","DOI":"10.4108\/eai.1-1-2016.150813"},{"key":"1537_CR10","doi-asserted-by":"crossref","unstructured":"Carli R, Cavone G, Ben S, Dotoli M (2020) IoT based architecture for model predictive control of HVAC systems in smart buildings. Sensors 20(3):781","DOI":"10.3390\/s20030781"},{"key":"1537_CR11","doi-asserted-by":"crossref","unstructured":"Bashir M, Gill A (2016) Towards an IoT big data analytics framework: smart buildings systems. In: Proc. IEEE 14th intl conference on smart city, pp 1325\u20131332","DOI":"10.1109\/HPCC-SmartCity-DSS.2016.0188"},{"key":"1537_CR12","doi-asserted-by":"publisher","unstructured":"Bernardi E, Morato M, Mendes P, Normey-Rico J, Adam E (2021) Fault-tolerant energy management for an industrial microgrid: a compact optimization method. Int J Electr Power Energy Syst. https:\/\/doi.org\/10.1016\/j.ijepes.2020.106342","DOI":"10.1016\/j.ijepes.2020.106342"},{"key":"1537_CR13","doi-asserted-by":"publisher","unstructured":"Morato M, Mendes P, Normey-Rico J, Bordons C (2020) LPV-MPC fault-tolerant energy management strategy for renewable microgrids. Int J Electr Power Energy Syst. https:\/\/doi.org\/10.1016\/j.ijepes.2019.105644","DOI":"10.1016\/j.ijepes.2019.105644"},{"issue":"2","key":"1537_CR14","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1109\/TVT.2016.2556691","volume":"66","author":"J Zhang","year":"2017","unstructured":"Zhang J, Yao H, Rizzoni G (2017) Fault diagnosis for electric drive systems of electrified vehicles based on structural analysis. IEEE Trans Veh Technol 66(2):1027\u20131039","journal-title":"IEEE Trans Veh Technol"},{"key":"1537_CR15","doi-asserted-by":"crossref","unstructured":"Kn\u00fcppel T, Blanke M, \u00d8stergaard J (2014) Fault diagnosis for electrical distribution systems using structural analysis. Int J Robust Nonlinear Control 24(8):1446\u20131465","DOI":"10.1002\/rnc.3080"},{"key":"1537_CR16","doi-asserted-by":"crossref","unstructured":"Sarrate R, Nejjari F, Rosich A (2012) Sensor placement for fault diagnosis performance maximization in distribution networks. In: Proc. 20th Mediterranean conference on control & automation, pp 110\u2013115","DOI":"10.1109\/MED.2012.6265623"},{"key":"1537_CR17","doi-asserted-by":"crossref","unstructured":"Leal R, Aguilar J, Trave-Massuyes L, R\u00edos A, Camargo E (2015) An approach for diagnosability analysis and sensor placement for continuous processes based on evolutionary algorithms and analytical redundancy. Appl Math Sci 9(43):2125\u20132146","DOI":"10.12988\/ams.2015.52122"},{"key":"1537_CR18","doi-asserted-by":"crossref","unstructured":"Chen Z, Xu J, Ke H, Fan X, Peng T (2021) Graph convolution network-based fault diagnosis method for the rectifier of the high-speed train. In: Proc. 4th IEEE international conference on industrial cyber-physical systems, pp 491\u2013497","DOI":"10.1109\/ICPS49255.2021.9468132"},{"issue":"6","key":"1537_CR19","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1109\/TSMCA.2006.878984","volume":"36","author":"L Trav\u00e9-Massuy\u00e8s","year":"2006","unstructured":"Trav\u00e9-Massuy\u00e8s L, Escobet T, Olive X (2006) Diagnosability analysis based on component supported analytical redundancy. IEEE Trans Syst Man Cybern 36(6):1146\u20131160","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"1537_CR20","doi-asserted-by":"crossref","unstructured":"Krysander M, \u00c5slund J, Frisk E (2010) A structural algorithm for finding testable sub-models and multiple fault isolability analysis. In: Proc. 21st intl. workshop on principles of diagnosis","DOI":"10.36001\/phmconf.2010.v2i1.1940"},{"issue":"6","key":"1537_CR21","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1109\/TSMCA.2010.2049993","volume":"40","author":"C Svard","year":"2010","unstructured":"Svard C, Nyberg M (2010) Residual generators for fault diagnosis using computation sequences with mixed causality applied to automotive systems. IEEE Trans Syst Man Cybern 40(6):1310\u20131328","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"1537_CR22","doi-asserted-by":"publisher","unstructured":"S\u00e1nchez M, Exposito E, Aguilar J (2020) Implementing self-autonomic properties in self-coordinated manufacturing processes for the industry 4.0 context. Comput Ind. https:\/\/doi.org\/10.1016\/j.compind.2020.103247","DOI":"10.1016\/j.compind.2020.103247"},{"key":"1537_CR23","doi-asserted-by":"crossref","unstructured":"Aguilar J, Salazar C, Velasco H, Monsalve-Pulido J, Montoya E (2020) Comparison and evaluation of different methods for the feature extraction from educational contents. Computation 8(2):30","DOI":"10.3390\/computation8020030"},{"issue":"1","key":"1537_CR24","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1109\/TSMCA.2007.909555","volume":"38","author":"M Krysander","year":"2008","unstructured":"Krysander M, \u00c5slund J, Nyberg M (2008) An efficient algorithm for finding minimal over-constrained subsystems for model-based diagnosis. IEEE Trans Syst Man Cybern A Syst Hum 38(1):197\u2013206","journal-title":"IEEE Trans Syst Man Cybern A Syst Hum"},{"key":"1537_CR25","doi-asserted-by":"crossref","unstructured":"Araujo M, Aguilar J, Aponte H (2003) Fault detection system in gas lift well based on artificial immune system. In: Proc. intl. joint conference on neural networks, vol 3, pp 1673\u20131677","DOI":"10.1109\/IJCNN.2003.1223658"},{"issue":"1","key":"1537_CR26","doi-asserted-by":"publisher","first-page":"1006","DOI":"10.1016\/j.ifacol.2017.08.208","volume":"50","author":"J Lunze","year":"2017","unstructured":"Lunze J (2017) A method to get analytical redundancy relations for fault diagnosis. IFAC-Pap Online 50(1):1006\u20131012","journal-title":"IFAC-Pap Online"},{"key":"1537_CR27","doi-asserted-by":"crossref","unstructured":"Armengol J, Bregon A, Escobet T, Gelso E, Krysander M, Nyberg M, Olive X, Pulido B, Trav\u00e9-Massuy\u00e8s L (2009) Minimal structurally overdetermined sets for residual generation. A comparison of alternative approaches. In: Proc. 7th IFAC symposium on fault detection, supervision and safety of technical processes, pp 1480\u20131485","DOI":"10.3182\/20090630-4-ES-2003.00241"},{"key":"1537_CR28","doi-asserted-by":"publisher","first-page":"16111","DOI":"10.1109\/ACCESS.2020.2966545","volume":"8","author":"L Morales","year":"2020","unstructured":"Morales L, Aguilar J, Garc\u00e9s-Jim\u00e9nez A, Gutierrez J, Gomez-Pulido J (2020) Advanced fuzzy-logic-based context-driven control for HVAC management systems in buildings. IEEE Access 8:16111\u201316126","journal-title":"IEEE Access"},{"key":"1537_CR29","doi-asserted-by":"crossref","unstructured":"Durand D, Aguilar J, R-Moreno M (2022) An analysis of the energy consumption forecasting problem in smart buildings using LSTM. Sustainability 14(20):13358","DOI":"10.3390\/su142013358"},{"key":"1537_CR30","unstructured":"Bhondekar A, Vig R, LalSingla M, Ghanshyam C, Kapur P (2009) Genetic algorithm based node placement methodology for wireless sensor networks. In: Proc. intl. multi conference of engineers and computer scientists, vol I"},{"issue":"1","key":"1537_CR31","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.enbenv.2020.05.007","volume":"2","author":"Q Zhao","year":"2021","unstructured":"Zhao Q, Lian Z, Lai D (2021) Thermal comfort models and their developments: a review. Energy Built Environ 2(1):21\u201333","journal-title":"Energy Built Environ"},{"key":"1537_CR32","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1016\/j.enbuild.2018.06.040","volume":"174","author":"H Zou","year":"2018","unstructured":"Zou H, Zhou Y, Yang J, Spanos C (2018) Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT. Energy Build 174:309\u2013322","journal-title":"Energy Build"},{"key":"1537_CR33","doi-asserted-by":"publisher","unstructured":"Quintero Y, Ardila D, Camargo E, Rivas F, Aguilar J (2021) Machine learning models for the prediction of the SEIRD variables for the COVID-19 pandemic based on a deep dependence analysis of variables. Comput Biol Med. https:\/\/doi.org\/10.1016\/j.compbiomed.2021.104500","DOI":"10.1016\/j.compbiomed.2021.104500"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-025-01537-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00607-025-01537-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-025-01537-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T07:46:53Z","timestamp":1758354413000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00607-025-01537-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,30]]},"references-count":33,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["1537"],"URL":"https:\/\/doi.org\/10.1007\/s00607-025-01537-5","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"type":"print","value":"0010-485X"},{"type":"electronic","value":"1436-5057"}],"subject":[],"published":{"date-parts":[[2025,8,30]]},"assertion":[{"value":"11 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}},{"value":"The content of this article does not reflect the official opinion of the European Union. Responsibility for the information and views expressed herein lies entirely with the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclaimer"}}],"article-number":"188"}}