A survey of data collaborative sensing methods for smart agriculture

Abstract

Data is becoming increasingly pivotal and foundational in the development of smart agriculture, underscoring the importance of efficient methods for obtaining high-value data. Data sensing methods have become the key technologies and methods to realize the agricultural Internet of Things (IoT). However, in the face of the new agricultural paradigm driven by big data, traditional agricultural IoT confronts numerous challenges at the data sensing level. This article, therefore, adopts a data sensing perspective and, based on the agricultural IoT, explores the evolution of data sensing technology in the agricultural domain. Initially, it introduces a data sensing framework for the agricultural Internet of Things, which integrates cloud and edge computing. Subsequently, it reviews the sensors commonly deployed in agricultural scenarios. Then, common methods for collaborative sensing of agricultural data were discussed from three aspects: intra-node, multiple nodes, and cross-domain. At the same time, the issues of data security and privacy in data collaborative sensing were discussed. Next, we integrate multi-dimensional technology to construct an application case for data sensing in the agricultural IoT. Finally, it discusses the challenges that Collaborative sensing technology encounters within the agricultural IoT.