Biomimetics is the interdisciplinary cooperation of biology and technology that offers solutions to practical problems by analyzing biological systems and transferring their principles into applications. This review article focused on biomimetic innovations, including bio-inspired soft robots and swarm robots that could serve multiple functions, including the harvesting of fruits, pest control, and crop management. The research demonstrated commercially available biomimetic innovations, including robot bees by Arugga AI Farming and the Robotriks Traction Unit (RTU) precision farming equipment. Additionally, soft robotic systems have made it possible to mitigate the risk of surface bruises, rupture, the crushing destruction of plant tissue, and plastic deformation in the harvesting of fruits with a soft rind such as apples, cherries, pears, stone fruits, kiwifruit, mandarins, cucumbers, peaches, and pome. Even though the smart farming technologies, which were developed to mimic nature, could help prevent climate change and enhance the intensification of agriculture, there are concerns about long-term ecological impact, cost, and their inability to complement natural processes such as pollination. Despite the problems, the market for bio-inspired technologies with potential agricultural applications to modernize farming and solve the abovementioned challenges has increased exponentially. Future research and development should lead to low-cost FEA robotic grippers and FEA-tendon-driven grippers for crop harvesting. In brief, soft robots and swarm robotics have immense potential in agriculture.

Information is the driving force of businesses because it can ensure the ability of knowledge and prediction. The railway industry produces a huge ume of data, with the proper processing of them and the use of innovative technology, there is the possibility of beneficial information to be provided which constitute the deciding factor for the correct decision making. Safety is the railway comparative advantage that has to be reinforced by each business administration while making the optimum decisions. The main purpose of this paper is the investigation of the most important dysfunctions that arise in a train and can cause its immobilization at the main passenger rail, resulting in huge delays of conducting the routes setting the passengers at risk. Afterwards the total of malfunctions is assessed and the most important, potentially, malfunction is assessed, so as the executives of the Greek Railway company to plan and redefine the processes and the initial plan of the predictive maintenance. This paper demonstrates the effort of implementing innovative applications by making use of methods from the rapidly developed field of Data Mining to the Greek Railway Company that uses obsolete procedures for the control of the trains' functionality in order to investigate the data for the provision of specialized information which will be used as a tool for the faster, more accurate and precise decision making. This decision making approach is based on a specific algorithm's design in order to automatically detect faults and make periodic maintenance of trains easier. Holistic approach is performed in the management of real data from the Greek railway industry and a predictive model of Machine Learning is developed, for the optimization of the management's performance of the trains reinforcing the strategic target of the railway industry which is the transportation of citizens with safety and comfort.

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The growing automation demands of production make the automation systems more complex and vulnerable to failures. For this reason, some instructions have been created (CAT, SIL) that must be followed, in order to insure their safe operation in case of a failure of both the hardware and the software. For a credible operation of a Fail Safety system along with a system to work on SIL2 or SIL3, must have Safety Hardware and Software. This present paper analyses the response of the Hardware of a Basic PLC and the equipment of an automation system. It also presents a descriptive analysis of the experiment, which was conducted to record measurements in order to draw firm conclusions. In addition, the measurements are analysed and evaluated to verify if basic equipment could be used in these systems and insure the Safety function at the same time. The objective is to simply prove that if we manage an already existing Basic PLC equipment differently, it could upgrade the security of automation systems. Therefore, with a low cost in time and money, particularly in existing automation systems, there could be Fail Safety operations.

In this paper, we gave information about introduction to the linear position sensors, their history and classification. In the content of this document, main parameter for this type of sensors are discussed while considering their application areas. Primary advantages or disadvantages of this kind of sensors are determined by their operating style and principle. Simulation result carried out in real life represents the comparison among these sensors. Those simulations are supplied with corresponding theoretical equations and formulas. Additionally, a novel read-out signal conditioning circuitry for Linear Variable Differential Transformers (LVDT) and Magnetostriction phenomenon are discussed and provided with specific instances.