The introduction of "smart machines" for agricultural operations will allow several advantages, such as an increase in their efficiencies, a reduction in environmental impacts and a reduction of work injuries. There are partially- and fully-automatic devices for most aspects of agricultural functions, from seeding and planting to harvesting, from spraying to livestock management, and so on. Moreover "precision farming", using sensors and robotic technologies are applied to existing systems. Work health and safety are also linked to the use of modern technologies, e.g., the protection of machinery operators from crush, entanglement, and shearing by means of mechatronic solutions. Another aspect is the use of robots and smart automation, which can also benefit from the gathering of operational data, such as machine condition and fleet monitoring, allowing preventive maintenance and improved fleet management. Considerable advances in sensing hardware, information technologies, smart systems, and software algorithms, have led to significant new developments in the areas of equipment health monitoring, fault diagnosis, and prognosis. These advances enable industries to undergo a fundamental shift towards condition-based maintenance to improve equipment availability and readiness at reduced operating costs throughout the system life-cycle. The emergence of sensor networks is also bringing the possibility of collective learning algorithms and decision-theoretic approaches to facilitate effective and scalable diagnostic/prognostic technology for widespread deployment of condition-based maintenance. The mentioned technological development is applicable to the relevant context of safety engineering. Furthermore, energy, safety and agriculture have an important role in reducing environmental emissions. All the systems aimed at the management of energy, safety, and environment are performed and optimized by means of innovative technologies, materials, processes, and methods.
VIII, 256 Seiten : Illustrationen, Diagramme
Printed Edition of the Special Issue Published in Agriculture