The increasing challenges of agricultural processes and the growing demand for food globally are driving the industrial agriculture sector to adopt the concept of ‘smart farming’. Smart farming systems, with their real-time management and high level of automation, can greatly improve productivity, food safety, and efficiency in the agri-food supply chain. This paper presents a customized smart farming system that uses a low-cost, low-power, and wide-range wireless sensor network based on Internet of Things (IoT) and Long Range (LoRa) technologies. In this system, LoRa connectivity is integrated with existing Programmable Logic Controllers (PLCs), which are commonly used in industry and farming to control multiple processes, devices, and machinery through the Simatic $IOT2040$. The system also includes a newly developed web-based monitoring application hosted on a cloud server, which processes data collected from the farm environment and allows for remote visualization and control of all connected devices. A Telegram bot is included for automated communication with users through this mobile messaging app. The proposed network structure has been tested, and the path loss in the wireless LoRa is evaluated.

In this article, a new efficient and robust approach—the high-resolution microwave imaging system—for early breast cancer diagnosis is presented. The core concept of the proposed approach is to employ a combination of a newly proposed delay-and-sum (DAS) algorithm and the specific absorption rate (SAR) parameter to provide high image quality of breast tumors, along with fast image processing. The new algorithm enhances the tumor response by altering the parameter referring to the distance between the antenna and the tumor in the conventional DAS matrices. This adjustment entails a much clearer reconstructed image with short processing time. To achieve these aims, a high directional Vivaldi antenna is applied around a simulated hemispherical breast model with an embedded tumor. The detection of the tumor is carried out by calculating the maximum value of SAR inside the breast model. Consequently, the antenna position is relocated near the tumor region and is moved to nine positions in a trajectory path, leading to a shorter propagation distance in the image-creation process. At each position, the breast model is illuminated with short pulses of low power waves, and the back-scattered signals are recorded to produce a two-dimensional image of the scanned breast. Several simulations of testing scenarios for reconstruction imaging are investigated. These simulations involve different tumor sizes and materials. The influence of the number of antennas on the reconstructed images is also examined. Compared with the results from the conventional DAS, the proposed technique significantly improves the quality of the reconstructed images, and it detects and localizes the cancer inside the breast with high quality in a fast computing time, employing fewer antennas.

The integration of Industry 4.0 technologies in agriculture will reduce the increasing challenges of agricultural process around the globe. The real-time farm management with high degree of automation will greatly improve productivity, agri-food supply chain efficiency and food safety. This paper describes a fully customized LoRa-based IoT system that aims for a low-cost, low power and wide range wireless sensor network targeted for smart farms. The presented system integrates already existing Programmable Logic Controllers (PLC) typically used to control multiple processes and devices such as water pumps, certain machinery, etc. along with a newly developed network of wireless LoRA sensors distributed over the farm. A Telegram bot is also included as novelty for automated user communication via this mobile phone messaging application. The network structure was deployed and tested. The developed integrated system also includes a cloud-based monitoring application to provide remote visualization and control for all the farming environment.

The rapid development of LoRa and LoRaWAN received a wide interest in research in order to understand the performance of this technologies for various IoT applications. In this article, we propose an IoT system for smart buildings based on LoRa and LoRaWAN. The main aim of this system is monitoring the moisture of wood in buildings; specifically, in cultural heritage buildings. Monitoring uses wireless sensor nodes that are digitally controlled and low-power. The wireless sensor node includes a moisture sensor that relies on a novel resistance measurement method which is developed and tested, including a new printed circuit board (PCB). The sensor comprises a LoRa communication module in order to be used as the end-node of the proposed system. To complete the monitoring system, a cloud-based application was developed to provide remote visualization and control for all LoRa sensor nodes in a building. The proposed system is scalable and represents a practical solution for early detection of wood moisture due to heavy rain, leaks, etc. The path loss is evaluated, showing that the proposed LoRa system can be applied for preservation of heritage buildings despite the attenuation of thick walls and complex architectural structures.