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Los espacios buscan atender unas condiciones de confort cada vez más exigentes y sin olvidar los criterios de eficiencia energética. En este sentido, los centros de cuidados de ancianos cobran vital relevancia y son un claro ejemplo donde las condiciones interiores y las mejoras a adoptar se centran en perseguir el bienestar del usuario. Además, este tipo de edificios, habitualmente comparten espacios de múltiples usos que dificulta establecer un criterio común de actuación. La presente comunicación analiza los trabajos llevados a cabo de monitorización en el marco de una auditoría energética de un centro gerontológico de propiedad pública. Un edificio caracterizado por sus grandes dimensiones en el que coexisten usos administrativos, sociales, servicios además del propio residencial. El objetivo perseguido por la monitorización era verificar y cuantificar el grado de disconfort térmico percibido por los usuarios y recabado en entrevistas previas. Dadas las particularidades del caso de estudio, el sistema implementado debía de ser capaz de superar las barreras generadas por las dimensiones del edificio y además ser un sistema de bajo coste y modular para poder ampliar las capacidades y puntos de monitorización. En cuanto a los resultados obtenidos, la monitorización ha permitido detectar y cuantificar las condiciones ambientales interiores de los espacios más representativos. Por otro lado, se ha podido verificar el correcto funcionamiento de la solución propuesta en su conjunto, así como detectar los puntos de mejora. Abstract Spaces seek to meet increasingly demanding comfort conditions without forgetting energy efficiency criteria. In this sense, care centres for the elderly are of vital importance and are a clear example where the interior conditions and the improvements to be adopted are focused on pursuing the user's wellbeing. In addition, this type of buildings usually shares spaces with multiple uses, which makes it difficult to establish a common criterion for action. This paper analyses the monitoring work carried out as part of an energy audit of a publicly owned gerontological centre. A building characterised by its large dimensions in which administrative, social, and service uses coexist in addition to residential use. The objective of the monitoring was to verify and quantify the degree of thermal discomfort perceived by the users and collected in previous interviews. Given the particularities of the case study, the system implemented had to be able to overcome the barriers generated by the dimensions of the building and also to be a low-cost and modular system in order to be able to extend the capacities and monitoring points. In terms of the results obtained, the monitoring has made it possible to detect and quantify the indoor environmental conditions of the most representative spaces. On the other hand, it has been possible to verify the correct operation of the proposed solution as a whole, as well as to detect points for improvement.

1. Information provided by tracking studies using remote telemetry is providing ecologists with invaluable new insights into animal behaviour and movement strategies. Here we describe a new type of GNSS (Global Navigation Satellite System) tracking device currently under development and nearing commercialisation, which transmits data via LoRaWAN (long range wide area network) gateways. These tags have the potential to be a low weight and power consumption solution for tracking the movement of animals at high resolution. 2. We characterise the position accuracy and data transmission range, including uplinks and downlinks, for the tracker using a series of ground-based field tests. Data transmission range was tested by visiting locations with line of sight to the LoRaWAN Gateway at distances up to 75 km and recording whether data transmission was completed successfully from each location. These tests were complemented by a trial deployment of six devices on griffon vultures Gyps fulvus. 3. These LoRa tags reliably provided accurate position estimates, particularly on more frequent acquisition cycles. At 1-min intervals the GNSS location bias was 4.71 m in the horizontal plane and 5 m in the vertical plane while precision, measured by standard deviation, was 3.9 m in horizontal space and 7.7 m in vertical space. Ground-based range tests confirmed data transmission from a maximum distance of 40.7 km. Initial results from a deployment on griffon vultures yielded useful information about flight speeds, altitude, and transmission range (up to 53.4 km). 4. With consistent GNSS position accuracy and the ability to transmit data over tens of kilometres, the LoRa tags demonstrated potential for monitoring animal movement over large areas. The small size and power needs of the device allow for flexibility in which combination of battery, solar panel, and housing they are paired with. The tags can be assembled in housing formats ranging in size from less than 5 g for deployment on Kestrel sized birds to 80 g for deployment on large birds such as vultures. The devices are particularly suitable for philopatric (site-faithful) species because LoRa gateways can be installed near breeding sites to maximise opportunities for data transmission. Our findings are informative for studies seeking to use LoRa for tracking birds and other animals using the miro-Nomad or a different type of GPS-LoRa logger. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) is one of the paradigms related to the evolution of telecommunication networks which is contributing to the evolution of numerous use cases, such as smart city and smart agriculture. However, the current communication infrastructure and wireless communication technologies are not always able to guarantee a proper service for these IoT scenarios. Smart solutions are needed to overcome current terrestrial network limitations offering a cost‐effective way to extend the current terrestrial network coverage. For example, temporary extensions "on‐request" of the terrestrial infrastructure may be a viable solution to allow collecting data generated by nodes outside the current network coverage. Flying objects can help achieve this goal. Various studies supported the use of unmanned aerial vehicles (UAVs) as intermediate nodes between IoT devices and the network. However, such solutions have not been exhaustively tested yet in real‐case scenarios. This paper proposes an efficient solution to collect data from multiple IoT sensors in rural and remote areas based on UAVs. It describes the implementation of the proposed UAV‐based Long RangeWide Area Network (LoRaWAN) flying gateway able to collect data directly from LoRaWAN sensors during its flight, keep them stored in an onboard memory, and forward them at the end of its flying path to a platform where the authorized users can access them. A prototype of the gateway has been developed to assess the proposed solution through both indoor and outdoor tests aiming to test its feasibility both in terms of communication performance and UAV‐required hardware resources. [ABSTRACT FROM AUTHOR]

Climate change is having an increasingly rapid impact on ecosystems and particularly on the issue of water resources. The Internet of Things and communication technologies have now reached a level of maturity that allows sensors to be deployed more easily on sites to monitor them. The communicating node based on LoRaWAN technology presented in this article is open and allows the interfacing of numerous sensors for designing long-term environmental monitoring systems of isolated sites. The data integration in the cloud is ensured by a workflow driving the storage and indexing of data, allowing a simple and efficient use of the data for different users (scientists, administration, citizens) through specific dashboards and extractions. This article presents this infrastructure through environmental monitoring use cases related to water resources. [ABSTRACT FROM AUTHOR]

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 I O T 2040 . 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. [ABSTRACT FROM AUTHOR]

Given the advantage of LoRaWAN private networks, multiple types of services have been implemented by users in one LoRaWAN system to realize various smart applications. With an increasing number of applications, LoRaWAN suffers from multi-service coexistence challenges due to limited channel resources, uncoordinated network configuration, and scalability issues. The most effective solution is establishing a reasonable resource allocation scheme. However, existing approaches are not applicable for LoRaWAN with multiple services with different criticalities. Therefore, we propose a priority-based resource allocation (PB-RA) scheme to coordinate multi-service networks. In this paper, LoRaWAN application services are classified into three main categories, including safety, control, and monitoring. Considering the different criticalities of these services, the proposed PB-RA scheme assigns spreading factors (SFs) to end devices on the basis of the highest priority parameter, which decreases the average packet loss rate (PLR) and improves throughput. Moreover, a harmonization index, namely HDex, based on IEEE 2668 standard is first defined to comprehensively and quantitively evaluate the coordination ability in terms of key quality of service (QoS) performance (i.e., PLR, latency and throughput). Furthermore, Genetic Algorithm (GA)-based optimization is formulated to obtain the optimal service criticality parameters which maximize the average HDex of the network and contribute to a larger capacity of end devices while maintaining the HDex threshold for each service. Simulations and experimental results show that the proposed PB-RA scheme can achieve the HDex score of 3 for each service type at 150 end devices, which improves the capacity by 50% compared to the conventional adaptive data rate (ADR) scheme. [ABSTRACT FROM AUTHOR]

An industrial wireless monitoring and control system, capable of supporting energy-harvesting devices through smart sensing and network management, designed for improving electro-refinery performance by applying predictive maintenance, is presented. The system is self-powered from bus bars, and features wireless communication and easy-to-access information and alarms. With cell voltage and electrolyte temperature measurements, the system enables real-time cell performance discovery and early reaction to critical production or quality disturbances such as short-circuiting, flow blockages, or electrolyte temperature excursions. Field validation shows an increase in operational performance of 30% (reaching 97%) in the detection of short circuits, which, thanks to a neural network deployed, are detected, on average, 10.5 h earlier compared to the traditional methodology. The developed system is a sustainable IoT solution, being easy to maintain after its deployment, and providing benefits of improved control and operation, increased current efficiency, and decreased maintenance costs. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) approach relies on the use of the Internet Protocol (IP) as a pervasive network protocol. IP acts as a "glue" for interconnecting end devices (on the field side) and end users, leveraging on very diverse lower-level and upper-level protocols. The need for scalability would suggest the adoption of IPv6, but the large overhead and payloads do not match with the constraints dictated by common wireless solutions. For this reason, compression strategies have been proposed to avoid redundant information in the IPv6 header and to provide fragmentation and reassembly of long messages. For example, the Static Context Header Compression (SCHC) protocol has been recently referenced by the LoRa Alliance as a standard IPv6 compression scheme for LoRaWAN-based applications. In this way, IoT end points can seamlessly share an end-to-end IP link. However, implementation details are out of the specifications' scope. For this reason, formal test procedures for comparing solutions from different providers are important. In this paper, a test method for assessing architectural delays of real-world deployments of SCHC-over-LoRaWAN implementations is presented. The original proposal includes a mapping phase, for identifying information flows, and a subsequent evaluation phase, in which flows are timestamped and time-related metrics are computed. The proposed strategy has been tested in different use cases involving LoRaWAN backends deployed all around the world. The feasibility of the proposed approach has been tested by measuring the end-to-end latency of IPv6 data in sample use cases, obtaining a delay of less than 1 s. However, the main result is the demonstration that the suggested methodology permits a comparison of the behavior of IPv6 with SCHC-over-LoRaWAN, allowing the optimization of choices and parameters during deployment and commissioning of both infrastructure components and software. [ABSTRACT FROM AUTHOR]

Solid waste management is one of the problems that has gained greater prominence in recent years. This topic has been discussed with greater emphasis in conjunction with environmental issues, driven by changes in the most diverse fields provided by the recent post-pandemic scenario. However, due to traditional or inefficient waste management approaches, most trash bins placed in cities can be seen as overflowing. Therefore, a remote monitoring system is needed to alert the level of garbage in bins to the relevant authority for waste clearance. In this scenario, the Internet of Things (IoT) paradigm plays a vital role in improving smart city applications by tracking and managing city processes. This paper implements a solution based on Low-Power Wide-Area Network (LPWAN) and blockchain technologies to provide the required data available for increasing efficiency in solid waste collection. Finally, this paper provides an evaluation of the proposed architecture related to latency and throughput metrics. [ABSTRACT FROM AUTHOR]

In the area of low-power wireless networks, one technology that many researchers are focusing on relates to positioning methods such as fingerprinting in densely populated urban areas. This work presents an experimental study aimed at quantifying mean location estimation error in populated areas. Using a dataset provided by the University of Antwerp, a neural network was implemented with the aim of providing end-device location. In this way, we were able to measure the mean localization error in areas of high urban density. The results obtained show a deviation of less than 150 m in locating the end device. This offset can be decreased up to a few meters, provided that there is a greater density of nodes per square meter. This result could enable Internet of Things (IoT) applications to use fingerprinting in place of energy-consuming alternatives. [ABSTRACT FROM AUTHOR]

In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications' range for End Devices (EDs). LoRa is a communication protocol that can cover a wide range with low energy consumption. To evaluate the efficiency of the LoRa Wide-Area Network (LoRaWAN), three criteria can be considered, namely, the Packet Delivery Rate (PDR), Energy Consumption (EC), and coverage area. A set of transmission parameters have to be configured to establish a communication link. These parameters can affect the data rate, noise resistance, receiver sensitivity, and EC. The Adaptive Data Rate (ADR) algorithm is a mechanism to configure the transmission parameters of EDs aiming to improve the PDR. Therefore, we introduce a new algorithm using the Multi-Armed Bandit (MAB) technique, to configure the EDs' transmission parameters in a centralized manner on the Network Server (NS) side, while improving the EC, too. The performance of the proposed algorithm, the Low-Power Multi-Armed Bandit (LP-MAB), is evaluated through simulation results and is compared with other approaches in different scenarios. The simulation results indicate that the LP-MAB's EC outperforms other algorithms while maintaining a relatively high PDR in various circumstances. [ABSTRACT FROM AUTHOR]

This paper aims at proposing an augmented sensing method for estimating volumetric water content (VWC) in soil for Internet of Underground Things (IoUT) applications. The system exploits an IoUT sensor node embedding a low-cost, low-precision soil moisture sensor and a long-range wide-area network (LoRaWAN) transceiver sending relative measurements within LoRaWAN packets. The VWC estimation is achieved by means of machine learning (ML) algorithms combining the readings provided by the soil moisture sensor with the received signal strength indicator (RSSI) values measured at the LoRaWAN gateway side during broadcasting. A dataset containing such measurements was especially collected in the laboratory by burying the IoUT sensor node within a plastic case filled with sand, while several VWCs were artificially created by progressively adding water. The adopted ML algorithms are trained and tested using three different techniques for estimating VWC. Firstly, the low-cost, low-precision soil moisture sensor is calibrated by resorting to an ML model exploiting only its raw readings to estimate VWC. Secondly, a virtual VWC sensor is shown, where no real sensor readings are used because only LoRaWAN RSSIs are exploited. Lastly, an augmented VWC sensing method relying on the combination of RSSIs and soil moisture sensor readings is presented. The findings of this paper demonstrate that the augmented sensor outperforms both the virtual sensor and the calibrated real soil moisture sensor. The latter provides a root mean square error (RMSE) of 3.33 % , a virtual sensor of 8.67 % , and an augmented sensor of 1.84 % , which improves down to 1.53 % if filtered in post-processing. [ABSTRACT FROM AUTHOR]

LoRaWAN networks rely heavily on the adaptive data rate algorithm to achieve good link reliability and to support the required density of end devices. However, to be effective the adaptive data rate algorithm needs to be tuned according to the level of mobility of each end device. For that purpose, different adaptive data rate algorithms have been developed for the different levels of mobility of end devices, e.g., for static or mobile end devices. In this paper, we describe and evaluate a new and effective method for determining the level of mobility of end devices based on machine learning techniques and specifically on the support vector machine supervised learning method. The proposed method does not rely on the location capability of LoRaWAN networks; instead, it relies only on data always available at the LoRaWAN network server. Moreover, the performance of this method in a real LoRaWAN network is assessed; the results give clear evidence of the effectiveness and reliability of the proposed machine learning approach. [ABSTRACT FROM AUTHOR]

The low power wide area networks (LPWANs) based on the LoRaWAN standard are suitable for Internet of Things (IoT) applications that involve a large number of low-power devices distributed over large areas. The LoRaWAN standard imposes some limitations on end-device configuration, such as the medium access strategies to be adopted, which depend on the region in which the network operates. In particular, in Europe, according to the ETSI regulations, a LoRaWAN end-device can use either a pure ALOHA medium access control (MAC) protocol or a polite medium access technique based on Listen Before Talk (LBT) Adaptive Frequency Agility (AFA). The aim of this work is to investigate the combined use of the two MAC protocols in the same LoRaWAN network. In particular, the work presents a simulative assessment of a LoRaWAN network that combines the use of Pure ALOHA and LBT AFA in realistic scenarios, under different workloads, when they work in compliance with the ETSI regulations. The work provides quantitative information that can help the network designer choose which protocol is more suitable for achieving the desired performance. [ABSTRACT FROM AUTHOR]

Agriculture Farming activity near to rivers and coastal areas sometimes imply spills of chemical and fertilizers products in aquifers and rivers. These spill highly affect the water quality in rivers' mouths and beaches close to those rivers. The presence of these elements can worse the quality for its normal use, even for its enjoying. When this polluted water reaches the sea can also have problematic consequences for fauna and flora. For this reason, it is important to rapidly detect where these spills are taking place and where the water does not have the minimum of quality to be used. In this article we propose the design and implementation of a LoRa (Long Range) based wireless sensor network for monitoring the quality of water in coastal areas, rivers and ditches with the aim to generate an observatory of water quality of the monitored areas. This network is composed by several wireless sensor nodes endowed with several sensors to physically measure parameters of water quality, such as turbidity, temperature, etc., and weather conditions such as temperature and relative humidity. The data collected by the sensors is sent to a gateway that forwards them to our storage database. The database is used to create an observatory that will permit the monitoring of the environment where the network is deployed. We test different devices to select the one that presents the best performance. Finally, the final solution is tested in a real environment for checking its correct operation. Two different tests will be carried out. The first test checks the correct operation of sensors and the network architecture while the second test show us the devices performance in terms of coverage. [ABSTRACT FROM AUTHOR]