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A Machine-Learning-Based IoT System for Optimizing Nutrient Supply in Commercial Aquaponic Operations.
Dhal, Sambandh Bhusan; Jungbluth, Kyle; Lin, Raymond; Sabahi, Seyed Pouyan; Bagavathiannan, Muthukumar; Braga-Neto, Ulisses; Kalafatis, Stavros.
Affiliation
  • Dhal SB; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 79016, USA.
  • Jungbluth K; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 79016, USA.
  • Lin R; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 79016, USA.
  • Sabahi SP; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 79016, USA.
  • Bagavathiannan M; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 79016, USA.
  • Braga-Neto U; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 79016, USA.
  • Kalafatis S; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 79016, USA.
Sensors (Basel) ; 22(9)2022 May 05.
Article in En | MEDLINE | ID: mdl-35591199
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nutrients / Ecosystem Type of study: Prognostic_studies Limits: Animals Language: En Journal: Sensors (Basel) Year: 2022 Document type: Article Affiliation country: United States
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nutrients / Ecosystem Type of study: Prognostic_studies Limits: Animals Language: En Journal: Sensors (Basel) Year: 2022 Document type: Article Affiliation country: United States