{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T05:08:53Z","timestamp":1775797733649,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004707","name":"Universiti Malaysia Perlis","doi-asserted-by":"crossref","award":["9001-00769"],"award-info":[{"award-number":["9001-00769"]}],"id":[{"id":"10.13039\/501100004707","id-type":"DOI","asserted-by":"crossref"}]},{"award":["9001-00769"],"award-info":[{"award-number":["9001-00769"]}],"id":[{"id":"https:\/\/ror.org\/00xmkb790","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>This study presents a nanosensor network system for autonomous microclimate optimization in precision horticulture, leveraging a field-programmable gate array (FPGA)-based control architecture that is integrated with an edge-level machine learning inference. Unlike the conventional greenhouse automation systems, which exhibit thermal and hygroscopic hysteresis often exceeding 32 \u00b0C and 78% relative humidity, the proposed framework embeds a random forest regression (RFR) model directly within the Altera DE2-115 FPGA fabric to enable predictive environmental regulation. The model achieved an R2 of 0.985 and root mean square error (RMSE) of 0.28 \u00b0C, allowing proactive compensation for the thermodynamic disturbances from the high-intensity light-emitting diode (LED) lighting with a 120 s predictive horizon. The real-time monitoring and remote supervision were supported via a NodeMCU-based IoT gateway, achieving a 140 ms mean communication latency and a 99.8% packet delivery reliability. The preliminary validation using lettuce (Lactuca sativa) optimized the environmental parameters, while the subsequent experiments with pepper (Capsicum annuum), a commercially important and environmentally sensitive crop, demonstrated system performance under real-world conditions. The control system maintained a temperature and humidity within \u00b10.3 \u00b0C and \u00b11.2% of the setpoints, respectively, and outperformed the baseline rule-based control with a 28% increase in fresh biomass, a 22% improvement in dry matter accumulation, a 25% reduction in actuator duty-cycle switching, and an 18% decrease in overall energy consumption. These results highlight the efficacy of FPGA-integrated edge intelligence combined with low-latency IoT telemetry as a scalable, energy-efficient, and high-fidelity solution for sub-degree environmental control in next-generation, controlled-environment, and vertical farming systems.<\/jats:p>","DOI":"10.3390\/info17040354","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T09:49:44Z","timestamp":1775641784000},"page":"354","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FPGA-Accelerated Machine Learning for Computational Environmental Information Processing in IoT-Integrated High-Density Nanosensor Networks"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3204-4070","authenticated-orcid":false,"given":"Alaa Kamal Yousif","family":"Dafhalla","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, College of Computer Science and Engineering, University of Ha\u2019il, KSA1, Hail 81451, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5390-2820","authenticated-orcid":false,"given":"Fawzia Awad Elhassan","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5809-3719","authenticated-orcid":false,"given":"Asma Ibrahim Gamar","family":"Eldeen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"}]},{"given":"Ikhlas Saad","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"}]},{"given":"Ameni","family":"Filali","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, College of Computer Science and Engineering, University of Ha\u2019il, KSA1, Hail 81451, Saudi Arabia"}]},{"given":"Amel Mohamed essaket","family":"Zahou","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7501-6854","authenticated-orcid":false,"given":"Amal Abdallah","family":"AlShaer","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5697-984X","authenticated-orcid":false,"given":"Suhier Bashir Ahmed","family":"Elfaki","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"}]},{"given":"Rabaa Mohammed","family":"Eltayeb","sequence":"additional","affiliation":[{"name":"College of Arts English Department, University of Ha\u2019il, Hail 81451, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1023-1780","authenticated-orcid":false,"given":"Tijjani","family":"Adam","sequence":"additional","affiliation":[{"name":"Faculty of Electronic Engineering & Technology, Universiti Malaysia Perlis (UniMAP), Arau 02600, Perlis, Malaysia"},{"name":"Micro System Technology, Centre of Excellence (CoE), Universiti Malaysia Perlis (UniMAP), Arau 02600, Perlis, Malaysia"},{"name":"Institute of Nano Electronic Engineering, Universiti Malaysia Perlis (UniMAP), Kangar 01000, Perlis, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s00521-025-11737-x","article-title":"FastML-GA: FPGA-accelerated machine learning for real-time energy HVAC optimization in buildings","volume":"38","author":"Mshragi","year":"2026","journal-title":"Neural Comput. 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