Data Science for Agricultural Innovation and Productivity

Author(s): Bogala Mallikharjuna Reddy * .

DOI: 10.2174/9789815196177124010007

Agriculture Robotics

Pp: 48-79 (32)

Buy Chapters
  • * (Excluding Mailing and Handling)

Data Science for Agricultural Innovation and Productivity

Agriculture Robotics

Author(s): Bogala Mallikharjuna Reddy * .

Pp: 48-79 (32)

DOI: 10.2174/9789815196177124010007

* (Excluding Mailing and Handling)

Abstract

In an agriculture-based society, where sustainable farming operations are required, quantitative field status and plant-by-plant monitoring may benefit all cultivators by enhancing farmland management. Sensing technology, artificial intelligence, autonomous robotics, and computerized data analytics will be important. In this book chapter, the essential features of using robotics in agriculture are presented; namely, the primary reasons for the automation of agriculture, the role of robotics in agriculture, its classification, evolution, and consideration of autonomous navigation for commercial agricultural robots, currently existing models of agriculture robots and their comparison, the potential benefits and limitations of agriculture robotics, gathering of massive data and using data science approaches for improving the food productivity and its influence on boosting the agriculture industry. The current study focuses on the adoption of agriculture robotics in the farming sector for various purposes (from land preparation to harvesting). The application of agriculture robotics for food production can favor the incorporation of agricultural robotics companies to minimize labor costs and food shortages. Furthermore, agriculture robotics can be the catalyst for new sources of information on the environmental impact (agroecological footprint) of the local food production chain.