Probabilistic Data Structure in smart agriculture

Abstract

In the modern world, the use of IoT devices and emerging technologies are contributing to a daily escalation in data generation. Numerous novel approaches are arising to handle such copious amounts of data. The utilization of this data in making decisions related to agriculture, combined with the integration of smart agriculture techniques, can enhance the conventional agricultural system. Smart agriculture relies heavily on the seamless integration and coordination of various devices. Data retrieval, storage, and analysis are some of the crucial tasks in this field. Data security, privacy, real-time decision-making, and semi-structured and unstructured data are some of the challenges and limitations of using traditional approaches when dealing with a high amount of generated data. For handling data and getting a real-time response in smart agriculture Probabilistic Data Structures (PDS) are used as an effective and efficient solution for various applications. Providing a thorough analysis of how PDS applications are utilized in the realm of smart agriculture is the main objective of this paper. This study takes an in-depth look into the important area of smart agriculture, examining its inception, obstacles, areas of research that require further exploration, and possible future paths. This paper aims to provide a comprehensive examination of PDS in smart agriculture, catering to readers and researchers who seek to expand their knowledge in this area. Additionally, this paper aims to identify potential research opportunities within this field.