首页|Research from Hassan II University Has Provided New Study Findings on Machine Le arning (Integrated Iot Approaches for Crop Recommendation and Yield-Prediction U sing Machine-Learning)
Research from Hassan II University Has Provided New Study Findings on Machine Le arning (Integrated Iot Approaches for Crop Recommendation and Yield-Prediction U sing Machine-Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from Casablanca, Morocco, by NewsRx correspondents, research stated, “In this study, we present an integr ated approach utilizing IoT data and machine learning models to enhance precisio n agriculture.”Our news journalists obtained a quote from the research from Hassan II Universit y: “We collected an extensive IoT secondary dataset from an online data reposito ry, including environmental parameters such as temperature, humidity, and soil n utrient levels, from various sensors deployed in agricultural fields. This datas et, consisting of over 1 million data points, provided comprehensive insights in to the environmental conditions affecting crop yield. The data were preprocessed and used to develop predictive models for crop yield and recommendations. Our e valuation shows that the LightGBM, Decision Tree, and Random Forest classifiers achieved high accuracy scores of 98.90%, 98.48%, and 9 9.31%, respectively. The IoT data collection enabled real-time moni toring and accurate data input, significantly improving the models’ performance. ”
Hassan II UniversityCasablancaMorocc oAfricaCyborgsEmerging TechnologiesMachine Learning
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