In this paper the authors discuss the realization of a Long Range Wide Area Network (LoRaWAN) network infrastructure to be employed for monitoring activities within the marine environment. In particular, transmission ranges as well as the assessment of parameters like Signal to Noise Ratio (SNR) and Received Signal Strength Indicator (RSSI) are analyzed in the specific context of an aquaculture industrial plant, setting up a transmission channel from an offshore monitoring structure provided with a LoRaWAN transmitter, to an ashore receiving device composed of two LoRaWAN Gateways. A theoretical analysis about the feasibility of the transmission is provided. The performances of the system are then measured with different network parameters (in particular the Spreading Factor—SF) as well as with two different heights for the transmitting antenna. Test results prove that efficient data transmission can be achieved at a distance of 8.33 km even using worst case network settings: this suggests the effectiveness of the system even in harsher environmental conditions, thus entailing a lower quality of the transmission channel, or for larger transmission ranges.

This paper presents the architecture and the performances of a Long Range Wide Area Network (LoRaWAN) infrastructure used for data transmission from a floating sensor node placed in the middle of the sea to a multi-Gateway structure positioned on the coast, whose purpose is the monitoring of offshore breeding cages within a fish farming plant. In particular, the sensor node is installed on a seamark buoy and it is interfaced with ad hoc sensors for the measurement of marine parameters. All sampled data are conveyed ashore to the Gateways by successfully covering the distance of 8.33 km. The paper presents the results concerning the performances of the data transmission for a 70 days operating period, analyzing the radio parameters (Signal-to-Noise Ratio - SNR and Received Signal Strength Indicator - RSSI) in relation with the variations of environmental parameters like temperature, relative humidity and atmospheric pressure as well as weather conditions. The proposed system demonstrates the usability of the LoRaWAN in all those cases where data collection from offshore monitoring structures is required: while this infrastructure focuses on the monitoring of fish farming plants, it may find application in several contexts, from navigational buoys to offshore oil plants.

In this article, we propose a reliable and low-latency Long Range Wide Area Network (LoRaWAN) solution for environmental monitoring in factories at major accident risk (FMAR). In particular, a low power wearable device for sensing the toxic inflammable gases inside an industrial plant is designed with the purpose of avoiding peculiar risks and unwanted accidents to occur. Moreover, the detected data have to be urgently and reliably delivered to remote server to trigger preventive immediate actions so as to improve the machine operation. In these settings, LoRaWAN has been identified as the most proper communications technology to the needs owing to the availability of off the shelf devices and software. Hence, we assess the technological limits of LoRaWAN in terms of latency and reliability and we propose a fully LoRaWAN compliant solution to overcome these limits. The proposed solution envisages coordinated end device (ED) transmissions through the use of Downlink Control Packets (DCPs). Experimental results validate the proposed method in terms of service requirements for the considered FMAR scenario.

Within the big picture of the Internet of Things (IoT) a brand new paradigm has risen since few years ago in the context of industrial scenarios: the Industrial Internet of Things (IIoT), whose aim is to transplant all of the features, characteristics and scopes of the IoT into industrial settings. The latter ones might be subject to a wide range of environmental conditions from the point of view of both temperature and relative humidity, along with harmful gases exposure and vibration due to, for instance, machineries. Therefore, whenever their monitoring is performed by means of devoted infrastructures, such extreme working conditions must be born in mind during the pertaining design phases. Mostly, industrial monitoring is put into effect by resorting to wireless sensor networks enabled by Low Power Wide Area Network (LPWAN) techonologies. This set of facilities includes an ample heterogeneity of standards and techniques. However, the Long Range (LoRa) modulation and the LoRa Wide Area Network (LoRaWAN) protocol extensively proved to be reliable and robust alternatives. Thus, in this paper the variations of hardware performances of a LoRaWAN sensor node, in terms of transmission capabilities, due to the changes of temperature and relative humidity, vibration and gaseous atmospheres like CO, NO and NO2, which are typical of industrial processes, are investigated. In so doing, an ageing process due to the aforementioned phenomena was induced. To this end, a measurement campaign within controlled environments (i.e., a climatic chamber, a fume extraction plant and an adhoc vibration test bench) was sorted out, whose results show a physiological performances drop that neither undermine the network reliability, nor damage the sensor node electronics.

In this work an IoT framework for the monitoring of chemical emissions in industrial plants is presented. The proposed system can embed different sensors. In particular, each sensor node manages a humidity sensor and an array of temperature and electrochemical gas sensors for the detection of CO, NO _x and O ₂ . Moreover it exploits some dedicated processing algorithms to compensate the dependence of the sensor response on temperature. The sensor node is provided with LoRa LPWAN connectivity that allows Wide Area data transmission: tests carried out in urban areas proved that a 3km communication range is achievable in noisy environments. A network architecture and a data acquisition and management structure is then presented for an application scenario in a Smart Industry context. A multilayer, modular topology is presented, combining the features of LoRa technology with shorter and larger range telecommunication channels, to develop an IoT framework that can be customized according to the physical and technical features of the deployment environment.

The safety of an operator working in a hazardous environment is a recurring topic in the technical literature of recent years, especially for high-risk environments such as oil and gas plants, refineries, gas depots, or chemical industries. One of the highest risk factors is constituted by the presence of gaseous substances such as toxic compounds such as carbon monoxide and nitric oxides, particulate matter or indoors, in closed spaces, low oxygen concentration atmospheres, and high concentrations of CO₂ that can represent a risk for human health. In this context, there exist many monitoring systems for lots of specific applications where gas detection is required. In this paper, the authors present a distributed sensing system based on commercial sensors aimed at monitoring the presence of toxic compounds generated by a melting furnace with the aim of reliably detecting the insurgence of dangerous conditions for workers. The system is composed of two different sensor nodes and a gas analyzer, and it exploits commercial low-cost commercially available sensors.