Agriculture plays an important role in the making and development of a country. In India, agriculture is the primary source of living for more than about 60% of its population. The... Show More

Agriculture plays an important role in the making and development of a country. In India, agriculture is the primary source of living for more than about 60% of its population. The agriculture-related issues always hinder the development of a country. The enhancement of traditional agriculture methods and its modernization towards smart agriculture is the only solution for agriculture problems. Hence, by considering this issue, a framework is presented for smart agriculture using sensor network and IoT. The key features of this system are the deployment of smart sensors for the collection of data, cloud-based analysis, and decision based on monitoring for spraying and weeding. The smart farming approach provides valuable collection of data, high precision control, and automated monitoring approach. The proposed system presents smart agriculture monitoring system that collects and monitors the soil moisture, environmental temperature, and humidity. The measured soil moisture, temperature, and humidity are stored in ThingSpeak cloud for analysis.

Recently, the basic functioning of monitoring in internet of things (IoT) is to apply the monitored data to the database for the regular analysis through mobile or computer platform. The purpose of... Show More

Recently, the basic functioning of monitoring in internet of things (IoT) is to apply the monitored data to the database for the regular analysis through mobile or computer platform. The purpose of this article is to highlight the application scope of IoT knowledge and to present the model of agricultural IoT for prediction by studying the influence of IoT technology towards modern agriculture. In order to explore the uncertain characteristics of the development of agricultural mechanization, the evaluation index system is simplified through the existing rough set theory. The neural network model is established with five random provinces and cities in 31 provinces and municipalities as test samples. By comparing the data of the neural network model established before and after the reduction, the results show that the index coefficient is reduced by about 60% based on the fixed information before and after the reduction. The simulation evaluation accuracy established by the artificial neural network model is 100%, which is consistent with the results of the original index system.

In order to solve the problems of high cost and difficult management of traditional agricultural planting, internet of things (IoT) technology was applied to realize real-time detection and... Show More

In order to solve the problems of high cost and difficult management of traditional agricultural planting, internet of things (IoT) technology was applied to realize real-time detection and intelligent management of crop growth and remote control of equipment, and change the traditional agricultural planting mode. The research results show that in MyEclipse development environment, using B/S (Browser/Server) architecture, Java and JavaScript language to design, Tomcat built server to publish information and complete the function of data storage and query, users can access the monitoring center in the local area network (LAN). When the detected data exceed the set threshold range, the control instructions issued by the monitoring center are transmitted to the main control chip through ethernet, and then the switching operation of the relay is controlled. The real-time monitoring of crop growth environment can be realized.

In this paper, an agricultural robot vision system is proposed for two typical environments—farmland and orchard—combined with weeding between crops. The system includes orchard production... Show More

In this paper, an agricultural robot vision system is proposed for two typical environments—farmland and orchard—combined with weeding between crops. The system includes orchard production monitoring and prediction tasks, the target information recognition approach, and visual servo decision making. The results obtained from the proposed system show that using the region combination features of image 2D histogram as the decision-making basis, the accurate and rapid indirect identification and positioning of crop seedlings can be accomplished while skipping the complex process of accurately identifying crops and weeds. The algorithm performs reasonably good as the time of target recognition in the prototype system is found to be less than 16 ms, and the average accurate recognition rate of 97.43% is achieved. The benefits of the proposed system are the continuous improvement of the quality of agricultural products, the rise of production efficiency, and the increase of economic benefits.

In order to quickly extract the visual navigation line of farmland robot, an extraction algorithm for dark primary agricultural machinery is proposed. The application of dark primary color principle... Show More

In order to quickly extract the visual navigation line of farmland robot, an extraction algorithm for dark primary agricultural machinery is proposed. The application of dark primary color principle in new farmland is made clearer by gray scale method, and the soil and crops are obviously separated, and the image processing technology of visual navigation line image of farmland is realized. In binary filtering of gray scale images, the maximum interclass variance method and morphological method are used respectively. The researchers use vertical projection method and least square method to the farmland interval extracted by navigation line. The farmland that needs the guide line image will be accurately located. It is found that the visual navigation extraction algorithm of farmland robot is widely used in the image extraction of navigation lines of various farmland roads and scenes compared with the traditional gray scale algorithm. Image processing has the advantages of clearer image processing.

To resolve the limited transmission and complicated layout, the common parameter measurement and control system of agricultural equipment use virtual instrument technology and embedded technology.... Show More

To resolve the limited transmission and complicated layout, the common parameter measurement and control system of agricultural equipment use virtual instrument technology and embedded technology. The research results show that the wireless transmission data of the system is accurate and reliable. The linearity errors of acquisition divestiture (AD) and frequency counting (FI) channel measurements are only 0.38% and 0.006%, respectively, and the resolution is 0.01V and 1 Hz. This performance evaluation fully meets equipment detection in agricultural use. The system is integrated with various wireless transmission platforms, intelligent agricultural equipment, and computer wireless reception and processing. These parameters can significantly improve the automation level and quality of agricultural equipment.