Computer Vision and Machine Learning-Based Predictive Analysis for Urban Agricultural Systems

Urban agriculture presents unique challenges, particularly in the context of microclimate monitoring, which is increasingly important in food production. This paper explores the application of convolutional neural networks (CNNs) to forecast key sensor measurements from thermal images within this context. This research focuses on using thermal images to forecast sensor measurements of relative air humidity, soil moisture, and light intensity, which are integral to plant health and productivity in urban farming environments. The results indicate a higher accuracy in forecasting relative air humidity and soil moisture levels, with Mean Absolute Percentage Errors (MAPEs) within the range of 10–12%. These findings correlate with the strong dependency of these parameters on thermal patterns, which are effectively extracted by the CNNs. In contrast, the forecasting of light intensity proved to be more challenging, yielding lower accuracy. The reduced performance is likely due to the more complex and variable factors that affect light in urban environments. The insights gained from the higher predictive accuracy for relative air humidity and soil moisture may inform targeted interventions for urban farming practices, while the lower accuracy in light intensity forecasting highlights the need for further research into the integration of additional data sources or hybrid modeling approaches. The conclusion suggests that the integration of these technologies can significantly enhance the predictive maintenance of plant health, leading to more sustainable and efficient urban farming practices. However, the study also acknowledges the challenges in implementing these technologies in urban agricultural models

Study of Load Characteristics of Various Types of Silicon PV Panels for Sustainable Energy Efficient Road Pavement

This paper presents a new approach to the creation of innovative roads having sustainable energy efficient road pavement as their basis. It is a new type of intelligent roads that is able to service itself and provide power, i.e. it is also a renewable source of electricity. It is planned to use the studies on the PV panels in sustainable energy efficient road pavement to determine their load parameters. The work used the methods of mathematical analysis and theoretical electrophysics to carry out the studies on load characteristics of various types of silicon PV panels in order to define the most effective panels from the point of view of generated electrical energy load resistance values. The analysis of the obtained results of the experimental research has shown that in order to make the operation of PV panels of series FS-100M and FS-110P most efficient, their load must be maintained within 3–3.5 Ω range. If load resistance exceeds the specified limits, the work of PV panels of this series will be ineffective. The road having a sustainable energy efficient road pavement is able to track road conditions, traffic, weather conditions and react quickly to their changes. It is shown how road markings can change dependance on road conditions

Wireless Sensor Networks: Towards Resilience Against Weather-Based Disruptions

The article discusses vulnerability of wireless sensors networks to weather-based disruptions considering the opinions of different experts published in a range of scientific materials. The introduction provides a brief overview of wireless signals in real world conditions focusing on how weather affects signals (rain, fog and clouds, snow, hail, lightning, wind, bodies of water, trees and physical obstruction). Information about the effects of weather on wireless sensor networks using Free Space Optical / Radio Frequency (FSO/RF) communication is then provided. Finally, the impact of weather conditions on MANET routing protocols is considered theoretically, and experimental simulations are performed by comparing the sustainability of different protocols to different weather conditions. After analysis of experiment results, ideas on how to decrease vulnerability of wireless networks to weather-based disruptions are discussed

Traffic Root Modelling and Assignment with Intelligent Transport System

The integration of emergency and specialized transport rooting tools in the usual traffic control paradigms is one of the opportunities offered by modern intelligent traffic control systems. The research is connected with improvement of on – line traffic control and adaptation of special traffic lighting alternatives by ITS The task can be solved with the help of modern technical methods and equipment as well as applying control paradigms of the distributed systems. The problem is solved with the help of calculations hyper-graph and scheduling theory. The goal the research is to develop methods, which support scheduling of the emergency transport, using high performance computing

Study of load characteristics of various types of silicon PV panels for sustainable energy efficient road pavement

This paper presents A new approach to the creation of innovative roads. Their basis is sustainable energy efficient road pavement-a new intellectual road that is able to service itself and provide power, ie  is also a renewable source of electricity. The PV panels studies are planned to be used in sustainable energy efficient road pavement to determine their load parameters. Knowing these parameters can ensure the transmission of the maximum power generated by PV panels into the load. In such systems, the load, and therefore its resistance, can dynamically change over time. Therefore, to ensure the most efficient operation of photovoltaic modules, it is necessary to constantly monitor the ratio of internal resistance PV panels and load resistance. Maintaining the equality of these resistances can provide the criterion of transmission of maximum power to the load. The work used methods of mathematical analysis and theoretical electrophysics to carry out studies of load characteristics of various types of silicon PV panels with the definition of the most effective from the point of view of generated electrical Energy load resistance values. The analysis of the obtained results of the experimental research has shown that in order to make the operation of PV panels of series FS-100M and FS-110P most efficient, their load must is maintained within 3-3.5 Ohm. If the load resistance will exceed the specified limits, the work of PV panels this series will be ineffective. The road consisting of sustainable energy efficient road pavement is able to track road conditions, traffic, weather conditions and react quickly to their changes. It is shown how road markings can change depending on road conditions

Wireless Sensor Networks: Towards resilience against Weather-based disruptions

The main aim of this article is to provide the information about vulnerability of wireless sensors networks to weather-based disruptions. Article is based on different expert’s opinions, published in a lot of scientific materials. All the useful references are given in references section. Introduction gives a short information about wireless signals in real world conditions – it is described how weather affects signals (rain, fog and clouds, snow, hail, lightning, wind, bodies of water, trees and physical obstruction). Information about the effects of weather on wireless sensor networks using Free Space Optical / Radio Frequency (FSO/RF) communication are then provided. Finally, the impact of weather conditions on MANET routing protocols are presented in theoretical manner, and experimental simulations are performed by comparing different protocols sustainability to different weather conditions. After investigation of experiment results, ideas about how to decrease a vulnerability of wireless networks to weather-based disruptions are discussed

Traffic Route Modelling and Assignment with Intelligent Transport System

The development of signal transmitting environment for multimodal traffic control will enhance the integration of emergency and specialized transport routing tools in usual traffic control paradigms - it is one of the opportunities offered by modern intelligent traffic control systems. The improvement of effective electric power use in public transport system is an advantage of Intelligent Transport System (ITS). The research is connected with the improvement of on-line traffic control and adaptation of special traffic lighting alternatives by ITS. The assignment of the nearest appropriate transport will be done by passenger request, but unlike information system, the transport planning is done on demand. The task can be solved with the help of modern technical methods and equipment, as well as by applying control paradigms of the distributed systems. The problem is solved with the help of calculations hyper-graph and scheduling theory. The goal of the research is to develop methods, which support scheduling of the emergency transport, using high performance computing

Development of Adaptive Control System for Aerial Vehicles

This article represents and compares two control systems for a vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV): a sliding proportional–integral–derivative (PID) controller and an adaptive L1 controller. The goal is to design a high-performing and stable control system for a specific VTOL drone. The mathematical model of the unique VTOL drone is presented as a control object. The sliding PID and adaptive L1 controllers are then developed and simulated, and their performance is compared. Simulation results demonstrate that both control systems achieve stable and accurate flight of the VTOL drone, but the adaptive L1 controller outperforms the sliding PID controller in terms of robustness and adaptation to changing conditions. This research contributes to ongoing work on adaptive control systems for VTOL UAVs and highlights the potential benefits of using L1 adaptive control for this application

Advanced practices: micro learning, practice oriented teaching and gamified learning

The development, introduction and evaluation of ICT based techniques have been at the forefront of educational reform of all levels for the last two decades. Microlearning, gamified learning are two novel ICT techniques most appropriate for e-learning material and programs which attracted renewed attention because of the CoVID-19 social distancing measures. Alongside those, the more established technique of practice-oriented learning is being revisited to adapt to the new challenges. This article presents the main results and conclusions of deliverable 3.1. of the ERASMUS+ Capacity Building for Higher Education project “Electrical Energy Markets and Engineering Education (ELEMEND)” which is devoted to training partner staff in micro learning, practice oriented teaching and gamified learning. After the goals of ELEMEND are presented in the light of modern engineering education, the concept of micro learning as a training paradigm is discussed. Next, gamification technology is described in view of its role in the educational process and specific implementation examples are given. Finally, the practice-oriented approach both in teaching and in learning with the methods used to carry on this approach is presented