Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence

Abstract

Precisely measuring the work area of agriculture farm machinery is important for performing the authentication of machinery usage, better allocation of resources, measuring the effect of machinery usage on the yield, usage billing and driver’s behaviour. The manual measurement, which is a common practice is an error-prone and time-consuming process. The irregular fields make it even more difficult to calculate the work area. An automatic solution that uses smart technology and algorithms to precisely calculate the work area is crucial for the advancement of agriculture. In this work, we have developed a smart system that utilizes the Internet of Things (IoT), Global Positioning System (GPS) and Artificial Intelligence (AI) that records the movement of agriculture machinery and use it to measure the precise work area of its usage. The system couples the nearest neighbourhood algorithms with Contact-based mechanisms to find the precise work area for different shaped fields and activities. The system was able to record the movement of machinery and calculate its work area, regardless of how many times the machinery runs through a particular field. Our evaluation shows that the system was able to precisely find the work boundaries and calculate the area with a maximum of 9% error for irregular shapes.

Energy Conservation for Internet of Things Tracking Applications Using Deep Reinforcement Learning

“…Machine learning is an excellent technique to overcome the computational complexity issue in any complicated engineering problem because it is a self-learner, and it does not need to be reprogrammed [ 32 , 33 , 34 , 35 ]. Based on background studies, there are three types of machine learning approaches (i.e., supervised, unsupervised, and reinforcement learning), which have been intelligently utilized for energy optimization.…”

Catalyzing Holistic Agriculture Innovation Through Industrial Biotechnology

“…215 Machine language represents the bulk of today's AI applications. 213 This is also true for agriculture research and innovation where one can find a diverse set of applications playing out in plant breeding, 216,217 plant pathology, [218][219][220] farm machinery, 221,222 and livestock production. 223,224 Machine learning is also playing a major role in areas such as antibiotic discovery, 225 omics, [226][227][228] and microbiome studies.…”

Designing and Manufacturing of Automatic Robotic Lawn Mower

“…Due to the shortage and aging of rural labor in recent years, agricultural production must rely on mechanization to improve production efficiency, but in order to improve labor productivity and to reduce production costs, automation and technicalization are the inevitable trend of agricultural development after agricultural mechanization [1]. The world is moving towards the fourth industrial revolution, and the latest technologies of IoT and AI, and Cloud Computing are becoming the mainstream [2]. Image processing plays a very important role in industrial production, which can visualize the anatomical structure of the product, can check and judge the advantages and disadvantages of the product in real-time, and reduce unnecessary losses to a certain extent [3].…”

“…From a service management perspective, the value of AI stems not from its virtual or unrecognized use but rather on the technology's ability to engage with customers at a social level [13]. With the rapid development of AI technology, intelligent robots have been widely used in various fields, such as agricultural management and water resources management [2,[14][15][16]. In the past, machine operators were isolated from machinery for safety reasons, but Industry 4.0 is designed to support future factories and reduce the tiredness of operators.…”

“…Agriculture is very important and indispensable to human beings, people must rely on agriculture to produce food, so there is a need for continuous supply and production to meet the needs of the growing population [2]. This study has designed a set of advanced image recognition technology to complete remote monitoring.…”