{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T16:34:48Z","timestamp":1772642088063,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,3]],"date-time":"2018-03-03T00:00:00Z","timestamp":1520035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"QREN","award":["SIDT 38798"],"award-info":[{"award-number":["SIDT 38798"]}]},{"DOI":"10.13039\/501100001871","name":"FCT","doi-asserted-by":"publisher","award":["ID\/EMS\/50022\/2013"],"award-info":[{"award-number":["ID\/EMS\/50022\/2013"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.<\/jats:p>","DOI":"10.3390\/app8030370","type":"journal-article","created":{"date-parts":[[2018,3,6]],"date-time":"2018-03-06T07:37:25Z","timestamp":1520321845000},"page":"370","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Wireless Sensors and IoT Platform for Intelligent HVAC Control"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6308-8666","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Ruano","sequence":"first","affiliation":[{"name":"Faculty of Science and Technology, University of Algarve, 8005-139 Faro, Portugal"},{"name":"IDMEC, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal"}]},{"given":"S\u00e9rgio","family":"Silva","sequence":"additional","affiliation":[{"name":"EasySensing\u2014Intelligent Systems, Centro Empresarial de Gambelas, University of Algarve, 8005-139 Faro, Portugal"}]},{"given":"Helder","family":"Duarte","sequence":"additional","affiliation":[{"name":"Faculty of Science and Technology, University of Algarve, 8005-139 Faro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2369-0115","authenticated-orcid":false,"given":"P.M.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"LaSIGE, Faculdade de Ci\u00eancias, Universidade de Lisboa, 1749-016 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1016\/j.rser.2014.11.066","article-title":"A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries)","volume":"43","author":"Nejat","year":"2015","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_2","unstructured":"(2015). Quadrennial Technology Review: An Assessment of Energy Technologies and Research Opportunities\u2014Chapter 1: Energy Challenges."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1016\/j.enbuild.2005.09.007","article-title":"Prediction of building\u2019s temperature using neural networks models","volume":"38","author":"Ruano","year":"2006","journal-title":"Energy Build."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/MCS.2011.2172532","article-title":"Predictive control for energy efficient buildings with thermal storage","volume":"32","author":"Ma","year":"2012","journal-title":"IEEE Control Syst. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1016\/j.jprocont.2013.08.009","article-title":"Thermal comfort control using a non-linear mpc strategy: A real case of study in a bioclimatic building","volume":"24","author":"Castilla","year":"2014","journal-title":"J. Process Control"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.enbuild.2015.06.002","article-title":"Model predictive control for indoor thermal comfort and energy optimization using occupant feedback","volume":"102","author":"Chen","year":"2015","journal-title":"Energy Build."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.enbuild.2015.03.045","article-title":"A neural network-based multi-zone modelling approach for predictive control system design in commercial buildings","volume":"97","author":"Huang","year":"2015","journal-title":"Energy Build."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.enbuild.2012.08.002","article-title":"Neural networks based predictive control for thermal comfort and energy savings in public buildings","volume":"55","author":"Ferreira","year":"2012","journal-title":"Energy Build."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.enbuild.2016.03.043","article-title":"The imbpc hvac system: A complete mbpc solution for existing hvac systems","volume":"120","author":"Ruano","year":"2016","journal-title":"Energy Build."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"31005","DOI":"10.3390\/s151229841","article-title":"An intelligent weather station","volume":"15","author":"Mestre","year":"2015","journal-title":"Sensors"},{"key":"ref_11","unstructured":"Ferreira, P.M., Pestana, R., and Ruano, A.E. (2015, January 22\u201324). Improving the Identification of RBF Predictive Models to Forecast the Portuguese Electricity Consumption. Proceedings of the 2nd IFAC Conference on Embedded Systems, Computer Intelligence and Telematics (CESCIT), Maribor, Slovenia."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/978-3-642-11739-8_2","article-title":"Evolutionary multiobjective neural network models identification: Evolving task-optimised models","volume":"Volume 372","author":"Ruano","year":"2011","journal-title":"New Advances in Intelligent Signal Processing"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1016\/S0967-0661(97)00136-6","article-title":"Fuzzy predictive control applied to an air-conditioning system","volume":"5","author":"Sousa","year":"1997","journal-title":"Control Eng. Pract."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ruano, A.E., Silva, S., Pesteh, S., Ferreira, P.M., Duarte, H., Mestre, G., Khosravani, H.R., and Horta, R. (2015, January 15\u201317). Improving a Neural Networks Based HVAC Predictive Control Approach. Proceedings of the 9th IEEE International Symposium on Intelligent Signal Processing (WISP 2015), Siena, Italy.","DOI":"10.1109\/WISP.2015.7139168"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.buildenv.2015.12.025","article-title":"Deducing the classification rules for thermal comfort controls using optimal method","volume":"98","author":"Hu","year":"2016","journal-title":"Build. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.apenergy.2015.10.061","article-title":"Potential of artificial neural networks to predict thermal sensation votes","volume":"161","year":"2016","journal-title":"Appl. Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1016\/j.asoc.2015.09.022","article-title":"Predictive control of multizone heating, ventilation and air-conditioning systems in non-residential buildings","volume":"37","author":"Garnier","year":"2015","journal-title":"Appl. Soft Comput."},{"key":"ref_18","unstructured":"ASHRAE (2004). Thermal Environmental Conditions for Human Occupancy, ASHRAE."},{"key":"ref_19","unstructured":"Fanger, P.O. (1972). Thermal Comfort: Analysis and Applications in Environmental Engineering, McGraw-Hill."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ferreira, P.M., Silva, S.M., Ruano, A.E., Negrier, A.T., and Conceicao, E.Z.E. (2012, January 10\u201315). Neural Network PMV Estimation for Model-Based Predictive Control of HVAC Systems. Proceedings of the 2012 IEEE International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia.","DOI":"10.1109\/IJCNN.2012.6252365"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1090\/qam\/10666","article-title":"A method for the solution of certain problems in least squares","volume":"2","author":"Levenberg","year":"1944","journal-title":"Q. Appl. Math."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1137\/0111030","article-title":"An algorithm for least-squares estimation of nonlinear parameters","volume":"11","author":"Marquardt","year":"1963","journal-title":"SIAM J. Appl. Math."},{"key":"ref_23","unstructured":"Ruano, A.E.B., Jones, D.I., and Fleming, P.J. (1991, January 11\u201313). A New Formulation of the Learning Problem for a Neural Network Controller. Proceedings of the 30th IEEE Conference on Decision and Control, Brighton, UK."},{"key":"ref_24","unstructured":"Ferreira, P.M., and Ruano, A.E. (2000, January 1\u20134). Exploiting the separability of linear and nonlinear parameters in radial basis function networks. Proceedings of the Adaptive Systems for Signal Processing,  Communications, and Control Symposium (AS-SPCC), Lake Louise, AB, Canada."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Penella, M.T., and Gasulla, M. (2007, January 1\u20133). A review of commercial energy harvesters for autonomous sensors. Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Warsaw, Poland.","DOI":"10.1109\/IMTC.2007.379234"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mateu, L., and Moll, F. (2005, January 9). Review of energy harvesting techniques and applications for microelectronics. Proceedings of the SPIE Microtechnologies for the New Millenium, Sevilla, Spain.","DOI":"10.1117\/12.613046"},{"key":"ref_27","unstructured":"Schaijk, R. (2011, January 7\u20139). Energy harvesting for wireless autonomous sensor systems. Proceedings of the 15th International Conference on Sensors and Measurement Technology (SENSOR 2011), Nurnberg, Germany."},{"key":"ref_28","unstructured":"Texas Instruments (2018, January 28). INA 126UA Instrumentation Amplifier. Available online: http:\/\/www.ti.com\/lit\/ds\/symlink\/ina126.pdf."},{"key":"ref_29","unstructured":"Low Power Radio Solutions (2018, January 28). N5AC-50108 Photo-Resistor. Available online: http:\/\/www.lprs.co.uk\/assets\/media\/Data Sheet O (N5AC-50108).pdf."},{"key":"ref_30","unstructured":"Microchip (2018, January 28). Mcp1700 Low Quiescent Current Voltage Regulator. Available online: http:\/\/ww1.microchip.com\/downloads\/en\/DeviceDoc\/21826b.pdf."},{"key":"ref_31","unstructured":"Texas Instruments (2018, January 28). TPS79901 Low Quiescent Current Voltage Regulator. Available online: http:\/\/www.ti.com\/lit\/ds\/symlink\/tps799-q1.pdf."},{"key":"ref_32","unstructured":"Jennic (2018, January 28). Aplication Note: JN-AN-1055, Using Coin Cells in Wireless Pans. Available online: http:\/\/www.jennic.com\/files\/support_documentation\/JN-AN-1055-Using-Coin-Cells-1v1.pdf."},{"key":"ref_33","unstructured":"Avago Technologies (2018, January 28). Apds-9007. Available online: http:\/\/docs.avagotech.com\/docs\/AV02-0512EN."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Guan, Y., Vasquez, J.C., Guerrero, J.M., Samovich, N., Vanya, S., Oravec, V., Garc\u00eda-Castro, R., Serena, F., Poveda-Villal\u00f3n, M., and Radojicic, C. (2017, January 6\u20139). An Open Virtual Neighbourhood Network to Connect IoT Infrastructures and Smart Objects\u2014Vicinity: IoT enables interoperability as a service. Proceedings of the 2017 Global Internet of Things Summit (GIoTS), Geneva, Switzerland.","DOI":"10.1109\/GIOTS.2017.8016233"},{"key":"ref_35","unstructured":"Silva, S. (2018, January 28). Easygateway. Available online: https:\/\/www.easysensing.pt\/static\/images\/easygateway_brocure_en.pdf."},{"key":"ref_36","unstructured":"Naranjo, P.G.V., Pooranian, Z., Shojafar, M., Conti, M., and Buyya, R. (2017). Fog-supported smart city network architecture for management of applications in the internet of everything environments. CoRR."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1109\/TII.2014.2300753","article-title":"Internet of things in industries: A survey","volume":"10","author":"Xu","year":"2014","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1109\/ACCESS.2015.2437951","article-title":"The internet of things for health care: A comprehensive survey","volume":"3","author":"Islam","year":"2015","journal-title":"IEEE Access"},{"key":"ref_39","unstructured":"Silva, S. (2018, January 28). Easymodule. Available online: https:\/\/www.easysensing.pt\/static\/images\/easymodule_brocure_en.pdf."},{"key":"ref_40","unstructured":"Silva, S. (2018, January 28). Easydatawebmonitor. Available online: https:\/\/www.easysensing.pt\/static\/images\/easydatawebmonitor_brochure_en.pdf."},{"key":"ref_41","unstructured":"Charles, K.E. (2003). Fanger\u2019s Thermal Comfort and Draught Models."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1016\/j.egypro.2015.07.218","article-title":"Thermal comfort analysis of pmv model prediction in air conditioned and naturally ventilated buildings","volume":"75","author":"Gilani","year":"2015","journal-title":"Energy Procedia"}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/8\/3\/370\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:57:27Z","timestamp":1760194647000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/8\/3\/370"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,3]]},"references-count":42,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2018,3]]}},"alternative-id":["app8030370"],"URL":"https:\/\/doi.org\/10.3390\/app8030370","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,3,3]]}}}