Towards Hybrid Smart Irrigation for Mixed-Cropping

Agricultural countries are facing water shortage problems. Due to mismanagement of the water distribution system and selection of inappropriate irrigation methods, water could be over- utilized that will affect crop production. Consequently, the economy of these countries could be badly affected. Moreover, water shortage problems also occur and the agriculturists bear financial losses as a result of this water scarcity. Existing irrigation systems are designed for specific crops cultivated in a season but that is not useful for other crops planned to be grown in the next season. Currently, the practice of mixed cropping is being used in the same agricultural field to gain more income in which farmers are growing vegetables with regular crops. For this practice, computerized systems are required for water scheduling among both crops. To cope up with these challenges, several Irrigation systems i. e. using WSNs, cloud- based, rule mining based and mobile-oriented solutions using GPRS have been proposed in the literature. These systems are functioning on unidirectional data focusing on a single irrigation system at a time, hence are unable to address factual solutions. There is a fundamental need to develop smart contextaware irrigation systems with the ability to deal with multicropping/mixed cropping in a particular field. In this paper, a smart context-aware irrigation system has been presented to deploy automated hybrid irrigation methods for mixed cropping practices to achieve more yield production. The system entails three major parts: 1) WSNs based data acquirement systems, 2) Decision Supports System and 3) Context-aware water scheduling. This system will help farmers in intensive farming of mixed cropping and cultivate large areas with less amount of water by applying three standard methods of irrigation according to the type and requirements of crops, land condition/soil types with context-awareness.

Automated summary

Agricultural countries are facing water shortage problems due to mismanagement of water distribution systems and inappropriate irrigation methods. Existing irrigation systems are unable to address the needs of mixed cropping in different seasons. This paper presents a smart context-aware irrigation system that utilizes automated hybrid irrigation methods to improve crop yield. The system includes data acquisition, decision support, and context-aware water scheduling components.