Affiliation:
1. Geetanjali College of Engineering and Technology, Hyderabad, India
2. National Institute of Fashion Technology, New Delhi, India
3. Galgotias University, Greater Noida, India
4. BIT Mesra, India
Abstract
Sensor-based intelligent recommender systems for agricultural activities are designed to provide personalized and context-aware recommendations to farmers, enabling them to make informed decisions and optimize their agricultural practices. These systems use the advancements in sensor technologies, data analytics, and machine learning algorithms to collect and analyze data from various agricultural sensors such as weather sensors, soil moisture sensors, and crop health sensors. This chapter presents an investigation into the development and application of sensor-based intelligent recommender systems for agricultural activities. The objective of this chapter is to enhance agricultural practices by using sensor technologies, data analytics, and machine learning algorithms. This chapter discusses collecting data from various agricultural sensors, including weather sensors, soil moisture sensors, and crop health sensors, to provide real-time information on environmental conditions and crop status.
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