INTELLIGENT WIRELESS TECHNOLOGY USAGE EFFECT IN CONTEXT OF PHYTOSANITARY TREATMENT SPRAYING

In agriculture, pesticides and fertilizers are applied to prevent crop disease and increase plant productivity. As a result of the digitalization of agriculture, human labor is increasingly interacting with intelligent technology through robots to facilitate agricultural operations. The use of intelligent technology protects the natural ecosystem by reducing the major damage caused by the unconventional application of phytosanitary treatments resulting in a flexible, proportional spraying at precise angles, thus avoiding the generation of large amounts of chemicals. This paper presents a short review about the state of the art of wireless sensors networks and how together with robotics can be applied in different fields of agriculture through the prism of sprayers that include a detection system and a wireless controlled spraye

Computational Contributions to the Automation of Agriculture

The purpose of this paper is to explore ways that computational advancements have enabled the complete automation of agriculture from start to finish. With a major need for agricultural advancements because of food and water shortages, some farmers have begun creating their own solutions to these problems. Primarily explored in this paper, however, are current research topics in the automation of agriculture. Digital agriculture is surveyed, focusing on ways that data collection can be beneficial. Additionally, self-driving technology is explored with emphasis on farming applications. Machine vision technology is also detailed, with specific application to weed management and harvesting of crops. Finally, the effects of automating agriculture are briefly considered, including labor, the environment, and direct effects on farmers

The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks

The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management

Geosensors to Support Crop Production: Current Applications and User Requirements

Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The present paper explores how sensors and sensor networks have been utilised in the crop production process and what their added-value and the main bottlenecks are from the perspective of users. The focus is on sensor based applications and on requirements that users pose for them. Literature and two use cases were reviewed and applications were classified according to the crop production process: sensing of growth conditions, fertilising, irrigation, plant protection, harvesting and fleet control. The potential of sensor technology was widely acknowledged along the crop production chain. Users of the sensors require easy-to-use and reliable applications that are actionable in crop production at reasonable costs. The challenges are to develop sensor technology, data interoperability and management tools as well as data and measurement services in a way that requirements can be met, and potential benefits and added value can be realized in the farms in terms of higher yields, improved quality of yields, decreased input costs and production risks, and less work time and load

Strategic Decision Making Under Uncertainty: Innovation and New Technology Introduction during Volatile Times1

Deere and Company, uncertainty, real option, organizational structure, option, risk, innovation, Industrial Organization, Risk and Uncertainty, Q1,

Ground and Aerial Robots for Agricultural Production: Opportunities and Challenges

Crop and animal production techniques have changed significantly over the last century. In the early 1900s, animal power was replaced by tractor power that resulted in tremendous improvements in field productivity, which subsequently laid foundation for mechanized agriculture. While precision agriculture has enabled site-specific management of crop inputs for improved yields and quality, precision livestock farming has boosted efficiencies in animal and dairy industries. By 2020, highly automated systems are employed in crop and animal agriculture to increase input efficiency and agricultural output with reduced adverse impact on the environment. Ground and aerial robots combined with artificial intelligence (AI) techniques have potential to tackle the rising food, fiber, and fuel demands of the rapidly growing population that is slated to be around 10 billion by the year 2050. This Issue Paper presents opportunities provided by ground and aerial robots for improved crop and animal production, and the challenges that could potentially limit their progress and adoption. A summary of enabling factors that could drive the deployment and adoption of robots in agriculture is also presented along with some insights into the training needs of the workforce who will be involved in the next-generation agriculture

Research status of agricultural robot technology

According to the different agricultural production uses, agricultural robots were classified, mainly including agricultural information collection robots, pruning robots, grafting robots, transplanting robots, spraying robots and picking robots. The research status of mainstream agricultural robots at home and abroad were introduced, and their working principles and characteristics were expounded. Finally, the problems existing in the key technologies of existing agricultural robots and their future development directions were put forward

Development trend of agricultural drone technology based on patent analysis

In recent years, global agricultural drone technology patent applications have continued to grow rapidly every year. In the global applicant rankings, the top 10 applicants are all Chinese applicants, with Chinese companies and universities far ahead. The patent applied for is mainly about operation management, which is closely related to the application scenarios of agricultural drones. In order to study the development trend of agricultural drone technology, the patent applications in the field of agricultural drone technology after 2009 were analyzed. The characteristics of agricultural drone technology patent activities are revealed from the perspectives of overall trends, geographical distribution, major competitors, and technical composition, and the development trend of agricultural drone technology is revealed from the perspective of patents. The results show that the agricultural drone technology is in the stage of technological development and has a bright future. In the next few years, the number of patent applications and applicants related to agricultural drone technology will continue to maintain a high growth trend. Overseas layout, improving the awareness of patent protection has become the focus. The research results can provide reference for the development of agricultural drone industry

Robots in Agriculture: State of Art and Practical Experiences

The presence of robots in agriculture has grown significantly in recent years, overcoming some of the challenges and complications of this field. This chapter aims to collect a complete and recent state of the art about the application of robots in agriculture. The work addresses this topic from two perspectives. On the one hand, it involves the disciplines that lead the automation of agriculture, such as precision agriculture and greenhouse farming, and collects the proposals for automatizing tasks like planting and harvesting, environmental monitoring and crop inspection and treatment. On the other hand, it compiles and analyses the robots that are proposed to accomplish these tasks: e.g. manipulators, ground vehicles and aerial robots. Additionally, the chapter reports with more detail some practical experiences about the application of robot teams to crop inspection and treatment in outdoor agriculture, as well as to environmental monitoring in greenhouse farming