Abstract
Smart farming uses advanced tools and technologies such as intelligent agricultural machines, high-precision sensors, navigation systems, and sophisticated computer systems to increase the economic benefits of agriculture and reduce the associated human effort. With the increasing demands of individualized farming operations, the internet of things is a crucial technique for acquiring, monitoring, processing, and managing the agricultural resource data of precision agriculture and ecological monitoring domains. Here, an internet of things-based system scheme integrating the most recent technologies for designing a management platform for agricultural machines equipped with automatic navigation systems is proposed. Various agricultural machinery cyber-models and their corresponding sensor nodes were constructed in a pre-production phase. Three key enabling technologies—multi-optimization of agricultural machinery scheduling, development of physical architecture and software, and integration of the controller-area-network with a mobile network—were addressed to support the system scheme. A demonstrative prototype system was developed and a case study was used to validate the feasibility and effectiveness of the proposed approach.
Highlights
The mass real-time demands of resource allocation as well as data processing in agriculture are currently placing new requirements on precision agriculture [1,2]
Internet of things (IoT) and cloud computing involve the basic management tasks of farming processes, and of visual data related to crop resources and growth environments [3,4]
This paper used the smart farm as an implementation scenario and proposed an IoT-enabled cloud management platform to manage and control the operation of agricultural machinery equipped with automatic navigation system
Summary
The mass real-time demands of resource allocation as well as data processing in agriculture are currently placing new requirements on precision agriculture [1,2]. Internet of things (IoT) and cloud computing involve the basic management tasks of farming processes, and of visual data related to crop resources and growth environments [3,4]. They are propelling the rapid development of smart farming. The farm management information system (FMIS), which includes the functions of data collection and analysis, decision making, and controlling variable rates, improves agricultural production and reduces negative impacts on the environment [5]. How to connect the FMIS to real smart farming has become a major issue
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