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Knowl. Discov. Data"],"published-print":{"date-parts":[[2025,6,30]]},"abstract":"<jats:p>\n            Honeybees, as natural crop pollinators, play a significant role in biodiversity and food production for human civilization. Bees actively regulate hive temperature (homeostasis) to maintain a colony\u2019s proper functionality. Deviations from usual thermoregulation behavior due to external stressors (e.g., extreme environmental temperature, parasites, pesticide exposure) indicate an impending colony collapse. Anticipating such threats by forecasting hive temperature and finding changes in temperature patterns would allow beekeepers to take early preventive measures and avoid critical issues. In that case, how can we model bees\u2019 thermoregulation behavior for an interpretable and effective hive monitoring system? In this article, we propose the\n            <jats:italic>principled<\/jats:italic>\n            Electronic Bee-Veterinarian Plus (EBV+) method based on the thermal diffusion equation and a novel \u201c\n            <jats:italic>sigmoid<\/jats:italic>\n            \u201d feedback-loop (P) controller for analyzing hive health with the following properties: (i) it is\n            <jats:italic>effective<\/jats:italic>\n            on multiple, real-world beehive time sequences (recorded and streaming), (ii) it is\n            <jats:italic>explainable<\/jats:italic>\n            with only a few parameters (e.g., hive health factor) that beekeepers can easily quantify and trust, (iii) it issues\n            <jats:italic>proactive<\/jats:italic>\n            alerts to beekeepers before any potential issue affecting homeostasis becomes detrimental, and (iv) it is\n            <jats:italic>scalable<\/jats:italic>\n            with a time complexity of\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(O(t)\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            for reconstructing and\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(O(t\\times m)\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            for finding\n            <jats:italic>m<\/jats:italic>\n            cuts of a sequence with\n            <jats:italic>t<\/jats:italic>\n            time-ticks. Experimental results on multiple real-world time sequences showcase the potential and practical feasibility of EBV+. Our method yields accurate forecasting (up to\n            <jats:italic>72%<\/jats:italic>\n            improvement in RMSE) with up to\n            <jats:italic>600<\/jats:italic>\n            times fewer parameters compared to baselines (ARX, seasonal ARX, Holt-winters, and DeepAR), as well as detects discontinuities and raises alerts that coincide with domain experts\u2019 opinions. Moreover, EBV+ is scalable and fast, taking less than\n            <jats:italic>1 minute<\/jats:italic>\n            on a stock laptop to reconstruct 2 months of sensor data.\n          <\/jats:p>","DOI":"10.1145\/3719014","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:56:01Z","timestamp":1740149761000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Principled Mining, Forecasting, and Monitoring of Honeybee Time Series with EBV+"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6534-358X","authenticated-orcid":false,"given":"Mst Shamima","family":"Hossain","sequence":"first","affiliation":[{"name":"University of California, Riverside, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2996-9790","authenticated-orcid":false,"given":"Christos","family":"Faloutsos","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1136-5967","authenticated-orcid":false,"given":"Boris","family":"Baer","sequence":"additional","affiliation":[{"name":"University of California, Riverside, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8553-732X","authenticated-orcid":false,"given":"Hyoseung","family":"Kim","sequence":"additional","affiliation":[{"name":"University of California, Riverside, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5462-9451","authenticated-orcid":false,"given":"Vassilis J.","family":"Tsotras","sequence":"additional","affiliation":[{"name":"University of California, Riverside, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,5,22]]},"reference":[{"key":"e_1_3_3_2_2","volume-title":"The Mathematics of Diffusion","author":"Crank J.","year":"1975","unstructured":"J. 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