The modelling of Linear Fresnel Collectors (LFCs) is crucial in order to predict accurate performance for annual yields and to define proper commands to design the suitable controller. The ISO 9806 modelling, applied to thermal collectors, presents some gaps especially with concentration collectors including LFCs notably due to the factorisation of the incidence angle modifiers and the fact that they are considered symmetric around the south meridian. The present work details the use of two alternative modellings methodologies based on recorded experimental data on the solar system installed at the Cyprus Institute, in the outskirts of Nicosia, Cyprus. The first modelling is the RealTrackEff, which is an improved ISO9806 modelling, and the second is constructed using the CARNOT blockset in MATLAB/Simulink. Both models include all the elements of the heat transfer fluid loop, i.e., mineral oil, with a tank and a heat-exchanger. First, the open loop’s studies demonstrated that the root mean square on temperature is 1 °C with the RealTrackEff; 2.9 °C with the CARNOT and 6.3 °C with the ISO9806 in comparison to the experimental data. Then, a PID control is applied on the experimental values in order to estimate the impact on the outlet temperature on the absorber and on power generation. Results showed that the error on the estimation of the heat absorbed reaches 32%.

This paper presents the design of a cost-effective online wireless monitoring system for two linear Fresnel reflector (LFR) solar plants located in two different countries. The first LFR plant is installed in the SEKEM medical center near Belbis city, Egypt, while the second is installed in the campus of the University of Palermo, Italy. The proposed system is a standalone system that reduces the interaction of labor as it offers online wireless monitoring for important parameters of the LFR such as solar irradiance, ambient temperature, outlet and inlet collector temperature and heat transfer fluid flow. For that purpose, a wireless sensor network (WSN) based on Arduino Mega boards coupled with XBee modules are used. The ZigBee XBee modules operate at 2.4 GHz, which have the advantages of being low cost and relatively low power consumption. The wireless nodes are supplied by solar paneled power banks, and send the data to a cloud in order to monitor both LFR plants remotely. The proposed system has been implemented and tested successfully before the future deployment on the LFR plants.

Semiconductor laser diode machining has emerged as a disruptive solution improving precision and efficiency in leather cutting making it an indispensable technology in industries such as automotive and aerospace. This study investigates the improvement of Normalized Performance Index (NPI) through the application of Extremum Seeking Control (ESC) to optimize the laser diode cutting process focusing on minimizing carbonization and kerf width while maximizing material removal rate (MRR) to improve the overall process efficiency. As this technology requires less power compared to conventional cutting methods and also reduce the overall carbon footprint promotes sustainability and supports ecofriendly manufacturing practices. The classic control techniques such as Linear-Quadratic Regulator (LQR) controllers and Proportional-Integral-Derivative (PID) controllers find it difficult to adjust to real-time process fluctuations. With adaptive real-time capabilities of ESC this approach offers a possible substitute by dynamically modifying parameters such as Pulse Width Modulation (PWM) and Stand-off Distance (SOD) to preserve the ideal cutting conditions. The impact of ESC on the Material Removal Rate (MRR), kerfwidth and carbonization of leather analysed in the proposed study. The results indicate that ESC considerably enhances the adaptability and consistency of the cutting process reducing carbonization and maintaining constant quality cut across varying conditions. These findings contribute to the advancement of semiconductor laser diode assisted leather cutting and proposes a unique technique for incorporating ESC into manufacturing processes for improved performance contributing to more sustainable and efficient leather cutting practices.

A Linear Fresnel Reflector (LFR) is a recent technology with good potential in small-scale solar power applications. It is composed of many long rows of mirrors that focus the sunlight onto a fixed elevated tubular receiver. Mirror segments are aligned horizontally and track the sun such that the receiver does not need to be moved. The efficiency with which the LFR can convert solar to thermal energy depends on the accuracy of the sun tracking system. To maximize the degree of sunlight capture, precise solar tracking is needed so that incident solar rays can be adequately focused to the focal point given by the location of the tubular receiver. The tilt angles of each row are relevant for the tracking controller to achieve correct positioning. Encoders are generally employed in closed-loop tracking systems as feedback signals used to inform the controller with the actual position of collector mirrors. Recently, inclinometers have begun to replace encoders as the most viable and cost-effective sensor technology solution; they offer simpler and more precise feedback, as they measure the angle of tilt with respect to gravity and provide the ability to adjust the system to the optimal angle for maximum output. This paper presents the research results on the development of remote measurements for the precise control of an LFR tracking system, by using distributed angle measurements. The applied methodology enables precision measurement LFR inclination angles through the fusion of data from multiple accelerometers, supported by low-cost wireless transceivers in a wireless sensor network, capable of exchanging information in a cloud infrastructure.

As cities strive to become more sustainable and livable in the age of smart urban development, there is a tendency toward urban landscaping concepts that combine ecological benefits and esthetic appeal. Within this context, artistic landscaping, the deliberate spatial arrangement of plant species to create visual compositions, has emerged as a valuable aspect of modern urban green infrastructure. While cutting-edge Unmanned Ground Vehicle (UGV) development has primarily focused on large-scale precision agriculture, its potential for artistic and small-scale urban landscaping remains unexplored. Furthermore, integrating Internet of Things (IoT) technology into UGVs for autonomous seeding presents an interesting research point. Addressing these challenges, this paper introduces a compact design of an IoT-enabled UGV specifically for artistic landscaping applications. The system includes an effective full seeding mechanism with dedicated modules for soil digging, sowing, water spraying, and backfilling. These operational modules are coordinated using a microcontroller-based control system to ensure reliability and repeatability. Additionally, in this study, a web-based interface has been developed to support both autonomous and manual operation modes, allowing users to customize path planning for geometric seeding patterns as well as real-time monitoring. A fully functional prototype was built and tested under controlled conditions to confirm the core modules’ effectiveness. This development provides a practical solution for supporting the realization of smart and sustainable cities.