{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T10:54:45Z","timestamp":1777287285747,"version":"3.51.4"},"reference-count":30,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,22]],"date-time":"2020-06-22T00:00:00Z","timestamp":1592784000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["760"],"award-info":[{"award-number":["760"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The increase in sensors in buildings and home automation bring potential information to improve buildings\u2019 energy management. One promissory field is load forecasting, where the inclusion of other sensors\u2019 data in addition to load consumption may improve the forecasting results. However, an adequate selection of sensor parameters to use as input to the load forecasting should be done. In this paper, a methodology is proposed that includes a two-stage approach to improve the use of sensor data for a specific building. As an innovation, in the first stage, the relevant sensor data is selected for each specific building, while in the second stage, the load forecast is updated according to the actual forecast error. When a certain error is reached, the forecasting algorithm (Artificial Neural Network or K-Nearest Neighbors) is trained with the most recent data instead of training the algorithm every time. Data collection is provided by a prototype of agent-based sensors developed by the authors in order to support the proposed methodology. In this case study, data over a period of six months with five-minute time intervals regarding eight types of sensors are used. These data have been adapted from an office building to illustrate the advantages of the proposed methodology.<\/jats:p>","DOI":"10.3390\/s20123524","type":"journal-article","created":{"date-parts":[[2020,6,23]],"date-time":"2020-06-23T09:05:33Z","timestamp":1592903133000},"page":"3524","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Use of Sensors and Analyzers Data for Load Forecasting: A Two Stage Approach"],"prefix":"10.3390","volume":"20","author":[{"given":"Daniel","family":"Ramos","sequence":"first","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"},{"name":"Polytechnic of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0848-5319","authenticated-orcid":false,"given":"Brigida","family":"Teixeira","sequence":"additional","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"},{"name":"Polytechnic of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5982-8342","authenticated-orcid":false,"given":"Pedro","family":"Faria","sequence":"additional","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"},{"name":"Polytechnic of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8597-3383","authenticated-orcid":false,"given":"Luis","family":"Gomes","sequence":"additional","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"},{"name":"Polytechnic of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4249-8367","authenticated-orcid":false,"given":"Omid","family":"Abrishambaf","sequence":"additional","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"},{"name":"Polytechnic of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4560-9544","authenticated-orcid":false,"given":"Zita","family":"Vale","sequence":"additional","affiliation":[{"name":"Polytechnic of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TSG.2016.2529424","article-title":"Modeling and valuation of residential demand flexibility for renewable energy integration","volume":"8","author":"Gottwalt","year":"2017","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Irfan, M., Zhao, Z.-Y., Ahmad, M., and Mukeshimana, M. (2019). Solar Energy Development in Pakistan: Barriers and Policy Recommendations. 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