The population of the world may reach almost 10 billion by 2050, and currently, approximately 37.7% of land is used for the production of crops. Agriculture is a major source of revenue for any country. Globally, automation in agriculture is in demand. Innovation and integration of technologies contributes for challenges faced by farmers with enlarged revenue and employment opportunities. Artificial intelligence has brought a revolution in agriculture. Crop wellbeing is important as it is a crucial factor that relates all parameters directly; therefore, crop health examination is mandatory. Premature detection of pests also reduces the quantity and frequent use of pesticides, but human intervention in process makes it time consuming and expensive. Time and techniques to use the pesticides in large farmland using AI along with computer vision and IoT converts traditional processes into smart agriculture. This chapter presents the assessment and implementation of an intelligent system for pesticide management.
TopIntroduction
Agriculture is India’s foundation. As per the Economic survey, modernization and automation is required in farming. Pests is one of the biggest issues as they can soil crops, with which every farmer has to struggle. Every year billions of USD loss are observed in crop due to disease and pests (Abhilash & Singh, 2009; Popp et al. 2013). To protect crop against pests, farmers used to spray pesticides regularly in farmland. Pesticides have numerous drawbacks also like it may harm farmers during spray sometimes may cause cancer, impact on consumer health due to supply chain and damage to non-infected crop (Grewal et al. 2017; Zang 2018). Excessive use of pesticides in crops also increases pesticides residue in food products and by controlling it, farmers pesticides expenditure can be reduced by around 90%.
Technology is contributing a vital role in agrobusiness. Involvement of many technologies in traditional agriculture has transformed it into digital agriculture. Artificial Intelligence is one of the promising technologies which can be used for pesticides management (Talaviya et al. 2020; Bannergee et al. 2018). If it is used accurately, it increases efficiency and reduces the adverse impact of pesticides on environment. Presently AI is costly and sometimes limit its applications into agriculture domain. These days many industries are working for it to reduce the initial cost, creating awareness and making eco-friendly devices so that wider population can be beneficial. Internet of Things (IoT) technology can be integrated for developing connected applications for farmers.
AI can support farmers to analyze multiple issues related with pest, climate, soil, water etc. Massive data handling with supreme precision is the strength of AI, which is used for decision making in harvesting (Panpatte 2018; Katiyar & Farhana 2021). Many tasks handled by human labor in agricultural lank such as pesticides spraying, weed removal, seed sowing. These tasks can be handled by AI through Robots, Drones, UAV (Schor et al., 2018; Ahirwar et al. 2019). These days farmers are using innovative approaches like AI, IoT and Computer Vision to protect their crops, increasing profits and sustainable farming (Arakeri et al. 2017; Elijah et al. 2018). These emerging technologies identify pests very precisely and pesticides spraying can be done at designated planes only.
Few challenges are there to implement such technologies like internet availability and awareness issues in rural areas (Abate et al. 2000). Once these challenges are overcome, pesticide management using AI will be observed as novel and feasible solution for crop protection from pests. The objective of this chapter to discuss about pesticides management i.e. partial and sufficient amount of pesticides must be applied on specified target area. Technologies intervention predict the possibility of disease and pest in future so action can be taken accordingly (Oluwole & Cheke, 2009; Bon et al., 2014). Soil and crops can be protected and hance farmers annual revenue must be increased.