Optimizing Smart Agriculture by Integrating Artificial Cognition: A Review, Current Challenges and Future Trends

Abstract

Agriculture is one of the most influential sectors for human existence given the fact that all human beings depend on food for survival. Hence there is continuous research for efficiency and effectiveness improvements in agricultural activities to yield a quality harvest with increased volumes. Rapid advancements in technologies have paved the way for smart agriculture to improve the agricultural process. Thus, many smart artifacts have been introduced to the agriculture field including autonomous robots. As a result, the agricultural aspects such as soil management, seeding, harvesting and plant disease management have been focused highly with the aim of upheaving each of these agricultural sectors. Since none of these systems are integrated with cognitive capabilities, they cannot operate in an optimal manner by taking rational decisions as humans on contemporary issues related to agriculture. Hence, these systems are less efficient and adaptive and become vulnerable in difficult conditions. Therefore, integration of cognition is vital to agricultural artifacts including robots and is a research challenge. A critical literature review has been carried out in this research to identify the existing limitations and challenges in smart agriculture and it was extensively discussed how cognition can be integrated in this regard. A hybrid cognitive architecture has been identified as a mechanism for integrating cognition into agricultural artifacts. Finally, the paper discusses several possible real-world applications with few case studies and provides insights for integrating cognition into agricultural artifacts.