• Energy Research

Rockfalls and landslides are hazards triggered from geomorphological and climatic factors other than human interaction. The economic and social impacts are not negligible, therefore the topic has become an important field in the application of remote monitoring. Wireless sensor networks (WSNs) are particularly suited for the deployment of such systems, thanks to the different technologies and topologies that are evolving nowadays. Among these, LoRa modulation technique represents a fitting technical solution for nodes communication in a WSN. In this paper, a smart autonomous LoRa-based rockfall and landslide monitoring system is presented. The structure has been operating in Pantelleria Island, Sicily, Italy. The sensing elements are disposed in sensor nodes arranged in a star topology. Network access to the LoRaWAN and the Internet is provided through gateways using a portable, solar powered device assembly. A system overview concerning both hardware and functionality of the nodes and gateways devices, then a power analysis is reported, and a monthly recorded result is presented, with related discussion.

Appropriate daylight control could maximize occupants’ visual comfort, potentially saving energy. However, the deployment of daylight control systems (DLCSs) is not happening, mainly due to the complex system calibration and the frequent reluctance of occupants toward automatic control systems that exclude their participation. In this paper, a human-in-the-loop DLCS is presented. The system is designed to allow the users to have direct interaction via smartphone Bluetooth communication, enabling them to set the lighting values deemed most comfortable nimbly. Special attention has been paid to the power consumption of the DLCS, especially in standby mode. Accessibility of configuration has been taken into consideration, leading to the choice of a wireless configured device. The performance of the prototype DLCS was evaluated experimentally in a side-lit room and compared with that of a commercial controller. The illuminance on a reference work plane was measured during the operation of the systems to observe the controllers’ effect on the lamp’s luminous flux while simultaneously considering the variation of daylight conditions. Moreover, the energy performance of the systems was studied to obtain information about the energetic effectiveness and convenience of the studied DLCSs. The main results showed that the proposed system could maintain the required target illuminance values on the work plane as daylight conditions vary: the maximum deviation measured using the prototype never exceeded 11 lx. In comparison, the commercial controller reached peaks of 220 lx. Moreover, the energy consumption of the prototype (resulting equal to 370 mVA) was lower than the consumption of the commercial system (equal to 600 mVA), allowing for increased energy savings over the long period. The more straightforward configuration allows the user to better interact with the DLCS.

In this paper, a novel integrated measuring and control system for hot box experiments is presented. The system, based on a general-purpose microcontroller and on a wireless sensors network, is able to fully control the thermal phenomena inside the chambers, as well as the heat flux that involves the specimen wall. Thanks to the continuous measurements of air and surfaces temperatures and energy input into the hot chamber, the thermal behavior of each hot box component is analyzed. A specific algorithm allows the post-process of the measured data for evaluating the specimen wall thermal quantities and for creating 2D and 3D thermal models of each component. The system reliability is tested on a real case represented by a double insulating X-lam wall. The results of the 72 h experiment show the system’s capability to maintain stable temperature set points inside the chambers and to log the temperatures measured by the 135 probes, allowing to know both the U-value of the sample (equal to 0.216 ± 0.01 W/m2K) and the thermal models of all the hot box components. The U-value obtained via hot box method has been compared with the values gathered through theoretical calculation and heat flow meter measurements, showing differences of less than 20%. Finally, thanks to the data postprocessing, the 2D and 3D thermal models of the specimen wall and of the chambers have been recreated.

It is necessary to ensure safety in terms of health and accidents through the real-time monitoring of the construction site environment and workers. This problem has become of great importance due to the economic and social implications. Therefore, a sensor-based approach has been found to be beneficial in Building Information Modeling (BIM). Wireless Sensor Network (WSN) technologies are well-suited for the deployment of monitoring systems. A suitable technical solution for node communication in a WSN is Long Range (LoRa) modulation technology. In this study, an autonomous LoRa-based system for the monitoring of a construction site in Lungro, Calabria, Italy, is presented. The spatial monitoring of working personnel is achieved by employing a tracker device with an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS) device. Accesses of personnel and gear to the site are registered using Radio Frequency Identification (RFID) tags equipped with protective gear. Fixed-position solar-powered sensor nodes are also employed for structural monitoring, i.e., movement sensors are used to monitor the variation of scaffolding, building structures, and under-work housing inclinations. Long Range Wide Area Network (LoRaWAN) gateways interface with the nodes and the internet for data exchange, enabling an Internet of Things (IoT) paradigm for the monitoring solution. A comprehensive overview of the workers and structural nodes, along with the RFID access management system and LoRaWAN gateway features, is provided in this article. A description of the web interface is also reported.

This paper deals with the definition and analysis of a complete electronic system for the detection and monitoring of stability characteristics in complex scenarios such as structural elements or environmental events. For instance, it may be successfully adopted to detect rockfall events on protection barriers, as well as to monitor landslides or the integrity of structures like bridges and buildings. The system is completely autonomous thanks to the implementation of an energy harvesting architecture and realizes a wireless sensor network whose nodes are auto-configurable, making it possible to freely arrange them in situ. The continuously collected data are relative to acceleration, inclination, position, and temperature of each node. These data are transmitted and stored on a remote web server devoted to the automatic management of alarms and accessible for data consulting. The proposed system is currently operating in different experimental fields in Italy.

The evaluation of photovoltaic (PV) system’s efficiency loss, due to the onset of faults that reduce the output power, is crucial. The challenge is to speed up the evaluation of electric efficiency by coupling the electric characterization of panels with information gathered from module diagnosis, amongst which the most commonly employed technique is thermographic inspection. The aim of this work is to correlate panels’ thermal images with their efficiency: a “thermal signature” of panels can be of help in identifying the fault typology and, moreover, for assessing efficiency loss. This allows to identify electrical power output losses without interrupting the PV system operation thanks to an advanced PV thermography characterization. In this paper, 12 faulted working panels were investigated. Their electrical models were implemented in MATLAB environment and developed to retrieve the ideal I-V characteristic (from ratings), the actual (operative) I-V characteristics and electric efficiency. Given the curves shape and relative difference, based on three reference points (namely, open circuit, short circuit, and maximum power points), faults’ typology has been evidenced. Information gathered from infrared thermography imaging, simultaneously carried out on panels during operation, were matched with those from electrical characterization. Panels’ “thermal signature” has been coupled with the “electrical signature”, to obtain an overall depiction of panels’ health status.

The use of Key Enabling Technologies (KET), in the definition of innovative systems, is a crucial point for smart industries and sustainability. The proposed work combines innovations from different fields, including industrial sustainability on the one hand, and smart electronics on the other. An innovative multifunctional panel is presented, produced with waste resulting from the industrial processing of paper and cardboard; the panel can be used for the control of safety in processing factories and for the monitoring of environmental conditions in the area, as well as the energy improvement of the building envelope. Several sensors are embedded in the panel for monitoring temperature, moisture, and localization by means of an RFID tag. In addition, the panel is battery–free, thus enhancing the installation and realization of the system. The power supply is provided by the tag reader as irradiated power, thus realizing a very low power application. Panels have been already realized and experimental tests have been performed in the laboratory.