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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works The Internet Engineering Task Force (IETF) has standardized a new framework for IPv6 support over Low Power Wide Area Networks (LPWANs), called Static Context Header Compression and Fragmentation (SCHC). SCHC includes acknowledgment (ACK)-based mechanisms for reliable fragmented packet transmission. For the latter, SCHC defines a Receiver-Feedback Technique (RFT), called Compressed Bitmap (CB), by which a receiver reports to the sender whether the fragments carrying a packet have been received or not. Such information is carried as ACK payload. Considering the extraordinary frame size and message rate constraints of LPWANs, ACK payload size becomes crucial. In this paper, we compare the performance of CB with that of several alternative RFTs, namely List of Lost Fragments (LLF), List of Deltas (LoD), and Uncompressed Bitmap (UB), where the latter is used as a benchmark. We evaluate the considered RFTs in terms of ACK size, number of Layer 2 (L2) frames needed to carry an ACK, and ACK Time on Air. Our analysis shows that the use of RFTs different from CB offers significant performance improvement in many scenarios. Furthermore, we provide guidance on which RFT should be used for different packet sizes, error rates and error patterns. This research is funded in part by the ERDF and the Spanish Government through project TEC2016-79988-P and project PID2019-106808RA-I00, AEI/FEDER, EU.

LoRaWAN (Long Range WAN) is one of the well-known emerging technologies for the Internet of Things (IoT). Many IoT applications involve simple devices that transmit their data toward network gateways or access points that, in their turn, redirect data to application servers. While several security issues have been addressed in the LoRaWAN specification v1.1, there are still some aspects that may undermine privacy and security of the interconnected IoT devices. In this paper, we tackle a privacy aspect related to LoRaWAN device identity. The proposed approach, by monitoring the network traffic in LoRaWAN, is able to derive, in a probabilistic way, the unique identifier of the IoT device from the temporal address assigned by the network. In other words, the method identifies the relationship between the LoRaWAN DevAddress and the device manufacturer DevEUI. The proposed approach, named DEVIL (DEVice Identification and privacy Leakage), is based on temporal patterns arising in the packets transmissions. The paper presents also a detailed study of two real datasets: i) one derived by IoT devices interconnected to a prominent network operator in Italy; ii) one taken from the literature (the LoED dataset in Bhatia et al. (2020)). DEVIL is evaluated on the first dataset while the second is analyzed to support the hypothesis under the DEVIL operation. The results of our analysis, compared with other literature approaches, show how device identification through DEVIL can expose IoT devices to privacy leakage. Finally, the paper also provides some guidelines to mitigate the user re-identification threats.

The Internet of Things asserts that several applications, such as smart cities or intelligent agriculture, can be based on various embedded systems programmed to do different tasks, by transferring data over a network from sensors to a server, where the information is stored and treated, supporting the decision-making process. In this context, LoRaWAN is an accurate network topology based on a wireless technology called LoRa that is capable of transmitting small data rates at a long range, using low-powered devices, making it ideal for the acquisition of climate variables, such as temperature and relative humidity. Applying this architecture to agriculture buildings can be very useful to guarantee indoor thermal comfort conditions. In this study, this technology is applied to a passive solar system composed by a high thermal inertia wall, defined as Trombe wall, with air vents provided in the massive wall to improve heat transfer by air convection, and an external shading device to avoid overheating during summer and heat losses during winter. It is intended to analyze the possibility to control the interiortemperature of a poultry brooding house given that, in the early stages of life, chickens need accurate climate conditions in order to enhance their growth and reduce their mortality rate. In brief, temperature values acquired by different sensors placed on the Trombe wall travel through a LoRaWAN wireless network and are received by an application that controls the actuators, in this case, the opening and closing of the Trombe wall air vents, while the external shading device is controlled locally.

Most IoT networks implement one-way messages from the sensor nodes to the “application host server” via a gateway. Messages from any sensor node in the network are sent when its sensor is triggered or at regular intervals as dictated by the application, such as a Smart-City deployment of LoRaWAN traps/sensors for rat detection. However, these traps can, due to the nature of this application, be moved out of signal range from their original location, or obstructed by objects, resulting in under 69% of the messages reaching the gateway. Therefore, applications of this type would benefit from control messages from the “application host server” back to the sensor nodes for enhancing their performance/connectivity. This paper has implemented a cloud-based AI engine, as part of the “application host server”, that dynamically analyses all received messages from the sensor nodes and exchanges data/enhancement back and forth with them, when necessary. Hundreds of sensor nodes in various blocked/obstructed IoT network connectivity scenarios are used to test our DXN solution. We achieved 100% reporting success if access to any blocked sensor node was possible via a neighbouring node. DXN is based on DNN and Time Series models.

The trend towards cities and urbanisation, which increases the number of people living in urban areas, requires local authorities to provide services and natural resources more efficiently and effectively and develop some strategies for a sustainable environment. The more effective use of resources, growing awareness of sustainable environment, climate confidence and motivation to make cities more livable is a new concept called Smart City. In this study, the proposed system supports the garbage collection of the city government and works with low budget, low energy, and free radio frequencies. The Internet of Things (IoT) sensor node is assembled, and the network is set up based on the long range wide area network protocol to connect it to the sample garbage bin and collect data. Instant data collection by this network is carried out through the IoT and is designed based on the collected data. The goal is to build an ideal system for smart garbage collection in cities and support sustainability in cities by integrating with the city government's information systems. The data received from the sensor nodes and the efficiency of the system were demonstrated for local governments. The main outcome of this research is to develop a practical smart city application with minimal resources and support local governments in their daily work. Moreover, how a low power wide area network communication network with a frequency of 868 MHz works in Istanbul (Turkey) will be investigated further and which alternative to cellular networks is the most suitable for excellent communication in smart cities will be studied.

While the Internet of Things continues to grow, the LoRaWAN standard is generating special interest due to its open-source nature, ultralow-power consumption and long-range connectivity. Recent works have explored the challenges of implementing LoRaWAN, with scalability being considered one of the major bottlenecks imposed by its Aloha-based medium access control (MAC) layer. Despite much on-going research on LoRaWAN scheduling aimed at alleviating this concern, experimental approaches are rarely found in the literature. In this work, we describe the steps taken and the technical issues overcome to move from a low-overhead synchronization and scheduling concept to its real-world implementation on top of LoRaWAN Class A. Accordingly, an end-to-end architecture was designed and deployed on top of STM32L0 MCUs, which communicate with a central entity responsible for providing synchronization metrics and allocating transmission slots on demand. The clock drift of devices was measured in a temperature-controlled chamber, which served as a basis to define slot lengths in the network. As a result, an operational end-to-end system was implemented and evaluated for different setup scenarios, with 10-ms accuracy being achieved. Our experimental results show significant improvements in packet delivery ratios with respect to Aloha-based setups, especially under high network loads (up to 29% for SF12), thereby demonstrating the feasibility of the presented approach.

The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing city processes in real-time. One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact on our society’s health and the environment. The traditional waste management process begins with waste created by city residents and disposed of in garbage bins at the source. Municipal department trucks collect garbage and move it to recycling centers on a fixed schedule. Municipalities and waste management companies fail to keep up with outdoor containers, making it impossible to determine when to clean them or when they are full. This work proposes an IoT-enabled solid waste management system for smart cities to overcome the limitations of the traditional waste management systems. The proposed architecture consists of two types of end sensor nodes: PBLMU (Public Bin Level Monitoring Unit) and HBLMU (Home Bin Level Monitoring Unit), which are used to track bins in public and residential areas, respectively. The PBLMUs and HBLMUs measure the unfilled level of the trash bin and its location data, process it, and transmit it to a central monitoring station for storage and analysis. An intelligent Graphical User Interface (GUI) enables the waste collection authority to view and evaluate the unfilled status of each trash bin. To validate the proposed system architecture, the following significant experiments were conducted: (a) Eight trash bins were equipped with PBLMUs and connected to a LoRaWAN network and another eight trash bins were equipped with HBLMUs and connected to a Wi-Fi network. The trash bins were filled with wastes at different levels and the corresponding unfilled levels of every trash bin were monitored through the intelligent GUI. (b) An experimental setup was arranged to measure the sleep current and active current contributions of a PBLMU to estimate its average current consumption. (c) The life expectancy of a PBLMU was estimated as approximately 70 days under hypothetical conditions.

Maintaining hand hygiene has been an essential preventive measure for reducing disease transmission in public facilities, particularly during the COVID-19 pandemic. The large number of sanitizer stations deployed within public facilities, such as on university campuses, brings challenges for effective facility management. This paper proposes an IoT sensor network for tracking sanitizer usage in public facilities and supporting facility management using a data-driven approach. Specifically, the system integrates low-cost wireless sensors, LoRaWAN, and cloud-based computing techniques to realize data capture, communication, and analysis. The proposed approach was validated through field experiments in a large building on a university campus to assess the network signal coverage and effectiveness of sensor operation for facility monitoring. The results show that a LoRaWAN created from a single gateway can successfully connect to sensors distributed throughout the entire building, with the sensor nodes recording and transmitting events across the network for further analysis. Overall, this paper demonstrates the potential of leveraging the IoT-based Sanitizer Station Network to track public health mitigation methods in a large facility, which ultimately contributes to reducing the burden of maintaining public health during and post-pandemic.

Nowadays, due to modernization or advancement in the Internet of Things (IoT) especially in the Healthcare area, we want to take care of our elders with some monitoring equipment, and the Internet of Things can play a significant role in it. The motivation of writing this paper is to collect the information of various existing Internet of Things Architecture and Communication Techniques used in Healthcare Monitoring System to observe that how efficiently, different researchers have used it. So we have studied different real-time health monitoring system based on diseases which are common in elderly people like diabetes, blood pressure, heart disease, sleep apnea, and cancer, etc. In this real-time health monitoring system, researchers introduced many new measures, communication techniques like ZigBee, Long-Range Wide Area Network (LoRawan), Radio Frequency Identification (RFID). Apart from this, it was also observed that remote monitoring system in Healthcare is incomplete without data processing and early prediction in such diseases. Though, Machine learning provides efficient techniques to extract knowledge from diagnostic medical datasets collected from the patients. That is why we highlighted the current role of various Machine Learning algorithms like Support Vector Machine, K-Nearest Neighbor, Random Forest, etc., for processing of Healthcare data and also helpful to predict the output more precisely.

International audience; Internet of things (IoT) technology is based on connecting each real object to the internet. Every single object is uniquely recognized and reachable over the network. IoT last mile connectivity is based on different communication technologies and protocols, where the majority is categorized as short-range networks that operate in ISM bands like Zigbee, Wi-Fi, and Bluetooth. Short-range technologies were successfully tested and deployed in different industrial sectors. However, in the energy sectors, the deployment is challenging in certain hard to reach areas where reliable last-mile connectivity is required between the home area network (HAN) smart meters and the meter data management system (MDMS). Therefore recently, Low Power Wide Area Network (LPWAN) technology implementations, which offer long-range connectivity, has emerged as a promising alternative for IoT in Energy applications. Within LPWAN, a variety of technology implementations exist and operate in licensed and unlicensed spectrum respectively like NB-IoT, LoRaWAN, and Sigfox. In this article, we discuss both the performance of LoRaWAN in a real-world environment and its deployment as a low-cost, long-range, and reliable last-mile solution for energy smart metering in urban area scenario where a short-range solution may not be the optimum one. Furthermore, a prototype that is adapted to the existing Lebanese traditional energy sector was developed to test LoRaWAN's usefulness in Lebanon.

Light or sunlight can be converted into electricity using solar panel technology. The measurement process is needed on current and voltage parameters to determine whether a solar panel is working correctly or not. The application of the Internet of Things (IoT) is a suitable method for monitoring efficiency measurements on solar panel performance in real-time by combining several computational components, protocols, and sensors to interact more quickly and help all activities become more efficient. One IoT technology that can work efficiently is the Long Range Wide Area Network (LoRaWAN). LoRa communicates using radio frequencies with a wide coverage range and has a low power consumption level. In this study, the implementation of LoRaWAN technology as a communication protocol between three series of nodes and one gateway in building a solar panel system is then visualized on a web that can monitor currents and voltages in the form of graphs and numbers. Displays notifications when there is a change in the condition of the large voltage from the solar panel can control the state of turning on or off the lights and turning off the whole node, and displaying a history of current and voltage readings. The functionality of the system will later be tested using black-box testing. There was also a distribution of questionnaires to 35 respondents to measure the level of agreement that the system designed was running well.

International audience; With the ever growing internet of things market, Low Power Wide Area Networks (LPWAN) become more and more attractive. Among the various LPWAN technologies, LoRa (and LoRaWAN) has drawn a lot of research attention with its great adaptation capability. In fact, its spectrum modulation spreading factor, transmission power, data rate, channel bandwidth,and coding rate are so many configurable parameters allowing to cope with a large number of use cases. In addition, through its ADR (Adaptive Data Rate) function, LoRa offers an interesting mechanism to self-adapt its configuration to its operational conditions. Several works have been carried out for extending ADR to further improve its performance for different use cases. LoRa has even been recently investigated on its capacity to support the mobility, although it is not originally designed for.In this paper, we first review the most significant ADR enhancements proposed in the literature, then describe our earlier E-ADR proposal [1] aiming at dealing with the node mobility use case. This paper also provides experimental performance evaluations of the reviewed ADR enhancements in a mobile node scenario, highlighting the unique feature of E-ADR.

In this paper we propose LoRaSyNc (LoRa receiver with SyNchronization and Cancellation), a second generation LoRa receiver that implements Successive Interference Cancellation (SIC) and time synchronization to improve the performance of LoRa gateways. Indeed, the chirp spread spectrum modulation employed in LoRa experiences very high capture probability, and cancelling the strongest signal in case of collisions can significantly improve the cell capacity. An important feature of LoRaSyNc is the ability to track the frequency and clock drifts between the transmitter and receiver, during the whole demodulation of the interfered frame. Due to the use of low-cost oscillators on end-devices, a signal cancellation scheme cannot result accurate without such a tracking, especially at the lower data rates. We validate the performance of LoRaSyNc in presence of collisions by implementing a receiver prototype on software-defined-radios, and perform several experiments in different realistic scenarios, by also comparing our receiver with commercial gateways. Finally, we simulate a cell deployment with one or more gateways, showing that the proposed scheme improves performance by almost 50% compared to a traditional receiver.

Owing to the recent research and development on the Internet-of-Things (IoT) and machine-to-machine (M2M) communication, wireless sensor networks have attracted considerable attention. Among these networks, low power wide area networks (LPWANs), which realize low power, low data rate, and wide communication area, are most commonly used for long-range communication. These networks adopt asynchronous random-access protocols, such as the pure ALOHA protocol in the medium access control (MAC) layer. Thus, there is a high possibility that multiple nodes transmit packets simultaneously on the same frequency channel, resulting in packet collisions. Carrier-sense multiple access/collision avoidance (CSMA/CA) and centralized resource allocation are effective for avoiding packet collisions. However, these schemes increase the energy consumption of battery-powered LPWAN nodes. In addition, LPWAN has a large coverage area; hence, there is a high possibility that the carrier sense will not work successfully. Thus, this paper proposes a simple but effective machine-learning-based scheme that tackles the packet collision problem by offsetting the transmission timings and avoiding unnecessary packet transmission in an autonomous decentralized manner. Each LPWAN node adjusts the transmission probability and timing using the Q-learning technique. The proposed scheme provides effective packet collision avoidance for LPWAN nodes without the need for an additional control signal. The computer simulation results show that the proposed scheme can improve the average packet delivery ratio (PDR) by 60% compared to the pure ALOHA protocol.

There are surplus applications in modern smart cities where localization of indoor environments is critical ranging from surveillance and trailing in smart structures to the localized wireless distribution of advertising content in shopping malls. These applications are only successful if a robust and cost-effective real-time system is developed for precise localization. Another aspect considered for indoor localization is power consumption. Recent wireless standards such as Bluetooth Low Energy (BLE) and LoRa consume less power which makes them a perfect candidate for indoor localization. This work aims to carry out an experimental evaluation which would help to decide which wireless standard i.e., Wi-Fi, Bluetooth Low Energy (BLE), and LoRa are most suitable for indoor localization. Experiments are carried out using trilateration in three multiple environments. RSSI is used to calculate the coordinates of a sensor node. Results obtained from the experiment show that Wi-Fi is most accurate with an average error of 0.54 m. LoRa is second most accurate with an average error of 0.62 m and BLE is the least accurate with an average error of 0.82 m. These results can be used to decide which wireless standard is best suited for indoor localization.

The long range wide area network (LoRaWAN) is one of the enabling technologies for low power wide area (LPWA) networks. In LoRaWAN, a node transmits its packet to a gateway (GW) in an autonomous and decentralized manner. The quantity of data that can be transmitted by each node is limited by the duty cycle (DC). Furthermore, it is not easy for the nodes to perform sophisticated techniques for increasing the data quantity due to their limited functionality, especially when the nodes are battery-powered. If the network size increases, packet collision may occur more frequently. Since the packet transmission drains the LoRaWAN nodes' battery, the packet collision results in a waste of limited power. Thus, it is necessary to develop a simple but effective transmission strategy that efficiently utilizes limited battery at each LoRaWAN node. This study proposes packet-level index modulation (PLIM), which is suitable for such LPWA networks. PLIM takes advantage of the sparse data packet transmission in time and the selection of a frequency channel among multiple ones by each node. A time slot and frequency channel combination is selected, i.e., the index, to increase the data quantity. For long-range communication, it is necessary to use a higher spreading factor (SF) in LoRaWAN, which results in a lower data rate due to the DC. The proposed PLIM can compensate for such data rate loss by taking advantage of the sparse transmission in time. Numerical evaluation elucidates that the proposed PLIM can increase the data quantity of LoRaWAN system without requiring any modification in the specification. When the SF is 10, the proposed PLIM can increase the data quantity up to 32.5%, compared to the conventional LoRaWAN system.

Long-Range Wide-Area Network (LoRaWAN) enables flexible long-range service communications with low power consumption which is suitable for many IoT applications. The densification of LoRaWAN, which is needed to meet a wide range of IoT networking requirements, poses further challenges. For instance, the deployment of gateways and IoT devices are widely deployed in urban areas, which leads to interference caused by concurrent transmissions on the same channel. In this context, it is crucial to understand aspects such as the coexistence of IoT devices and applications, resource allocation, Media Access Control (MAC) layer, network planning, and mobility support, that directly affect LoRaWAN’s performance. We present a systematic review of state-of-the-art works for LoRaWAN optimization solutions for IoT networking operations. We focus on five aspects that directly affect the performance of LoRaWAN. These specific aspects are directly associated with the challenges of densification of LoRaWAN. Based on the literature analysis, we present a taxonomy covering five aspects related to LoRaWAN optimizations for efficient IoT networks. Finally, we identify key research challenges and open issues in LoRaWAN optimizations for IoT networking operations that must be further studied in the future.

The article discusses IoT based solutions to improve waste collection and monitoring in public waste containers. The paper examines whether the monitoring system used in the measurement process can be used to monitor the filling of containers. The system consists of a wireless module connected to an ultrasonic sensor. The data sent makes it possible to calculate the empty space in the waste containers. The values are obtained by measuring the distance from the top of the container to the surface of the waste. Low-power long-distance broadband network (LoRaWAN) transmitters were used for data transmission. The aim of the research: to test an inexpensive monitoring system and to describe a new system of sensors and transmitter modules. The system is characterized by extremely low power consumption and a wide range of sensors used. Measurements were performed in Vilnius. Containers of two types of sizes were analyzed, measurements were performed at five points of horizontal cross section of the containers. The study was performed at two different levels of container filling. The results show that an ultrasonic sensor can representatively measure waste filling depths at different levels of container filling. Based on the results, this sensor can be recommended in the intelligent waste management market. Such a system can provide the necessary data for optimizing waste collection processes in cities and avoid container overcrowding problems. Article in Lithuanian. Atliekų konteinerių užpildymo lygio matavimas naudojant daiktų interneto ir „LoRaWAN“ technologijos mažos galios jutiklius Santrauka Straipsnyje aptariami daiktų interneto jutikliais pagrįsti sprendimai, gerinantys atliekų surinkimą ir stebėjimą viešuose atliekų konteineriuose. Straipsnyje nagrinėta, ar matavimo procese naudojama stebėjimo sistema gali būti pritaikyta konteinerių užpildymui stebėti. Sistemą sudaro belaidis modulis, sujungtas su ultragarsiniu jutikliu. Siunčiami duomenys leidžia apskaičiuoti tuščią vietą atliekų konteineriuose. Vertės gaunamos matuojant atstumą nuo konteinerio viršaus iki atliekų paviršiaus. Duomenims perduoti panaudoti mažaenergiai tolimojo plačiajuosčio tinklo (LoRaWAN) siųstuvai. Tyrimo tikslas – išbandyti nebrangią stebėjimo sistemą bei apibūdinti naują jutiklių ir siųstuvų modulių sistemą. Sistemos vartojamos elektros energijos sąnaudos yra itin mažos, naudojamų jutiklių spektras gana platus. Matavimai atlikti Vilniaus mieste. Analizuoti dviejų dydžių tipų konteineriai, matavimai atlikti penkiuose konteinerių horizontalaus pjūvio taškuose. Tyrimas atliktas esant dviem skirtingiems konteinerių užpildymo lygiams. Rezultatai rodo, kad ultragarso jutiklis gali reprezentatyviai matuoti atliekų užpildymo gylius, esant skirtingam konteinerių užpildymo lygiui. Atsižvelgiant į rezultatus, galima rekomenduoti šį jutiklį intelektualiojoje atliekų tvarkymo rinkoje. Tokia sistema gali suteikti reikiamų duomenų atliekų surinkimo procesui optimizuoti miestuose ir išvengti konteinerių perpildymo problemų. Reikšminiai žodžiai: konteineriai, atliekų tvarkymas, „LoRaWAN“, daiktų interneto jutikliai.

This paper discusses how to address and overcome some of the problems related to smart data generation and visualization, such as the poor autonomy of wireless sensor devices and the flexibility of the data management platform. We described the implementation and field experiment of a modular IoT application for Smart-Farming, in which the sensor devices are powered by an on-board battery and the data management system is based on a highly flexible software stack, capable of displaying time series graphs and processing millions of data per second. The experiment shown that the power consumption of the sensor devices depends on many factors and that the lifecycle of the devices can reach years using ultra-low power processors, low power wide area network (LPWAN) such as LoRaWAN and a mix of energy saving techniques. The data management and visualization platform shown to be able to display many types of time-series graphs, deal with a wide variety of data-sources and effectively manage a large amount of data.

In recent years, Internet of Things (IoT) as an essential infrastructure for industrial development, environmental protection and human life enhancement has attracted researchers' attention. Currently, there are four hot research topics in IoT fields, including sensor design, communication scheme, secure transmission, and data mining. The LoRaWAN, an unlicensed band based long range wide area network specification, is very suitable for the activities or operations in an IoT environment due to its low power and long range communication. In the LoRaWAN, star-of-stars topology, asynchronous communication, and three communication modes are used to reduce its power consumption. In order to enhance the security of network communication, the LoRaWAN adopts the 128-bit Advanced Encryption Standard (AES-128) and utilizes two session keys: network session key and application session key, for encrypting/decrypting data between end devices and network/application servers. However, according to the LoRaWAN Backend Interfaces 1.0 Specification announced by LoRa Alliance in 2017, the application layer communication securities between two arbitrary servers (including network servers, join server, and application servers) are out of the specification's scope. That is to say that the important data transmitted from one server to another may be attacked, falsified, or stolen easily. In this paper, a session key generation method is proposed to generate session keys with which two servers can securely communicate with each other, especially enhancing the application layer communication securities undefined in the LoRaWAN Specification. By integrating elliptic curve cryptography and AES-128, the session keys for different pairs of servers are created. The security discussion shows that the proposed method provides the features of mutual authentication, confidentiality and message integrity. Besides, it can also help to resist replay and eavesdropping attacks.

Internet of Things (IoT) deployments are on the rise globally with Low Power Wide Area Networks (LPWAN) providing the wireless networks needed for this expansion. One of these technologies namely Long Range Wide Area Network (LoRaWAN) has proven to be a very popular choice. The LoRaWAN protocol allows for confirmed traffic from the end device to the gateway (uplink) and the reverse (downlink), increasing the number of IoT use cases that it can support. However, this comes at a cost as downlink traffic severely impacts scalability due to in part a gateway's duty cycle restrictions. This paper highlights some of the use cases that require confirmed traffic, examines the recent works focused on LoRaWAN confirmed traffic and discusses the mechanism with which is implemented. It was found that confirmed traffic is viable in small networks, especially when data transfer is infrequent. Additionally, the following aspects negatively impact the viability of confirmed traffic in large networks: the duty cycle restrictions placed on gateways, the use of spreading factor 12 for receive window 2 transmissions, a high maximum number of transmissions (NbTrans) and the ACK_TIMEOUT transmission backoff interval. The paper also raises and suggests solutions to open research challenges that must be overcome to increase the viability of confirmed traffic.

In modern monitoring systems, it is essential to deploy sensor nodes and deliver related data to the information center. Wireless sensor networks (WSNs) usually work in harsh environments with vibration, temperature variations, noise, humidity, and so on. The batteries of sensor nodes are always not replaceable because of difficult access. Most of existing literature tries to prolong network lifetime by improving sleep scheduling strategies and deployment methods, independently or jointly. However, the congenital defects of mesh network can’t be avoided completely. To overcome the technology challenges, this paper develops a LoRaWAN-based WSN and investigates its energy efficient scheduling method. Firstly, the basics and the limits of LoRaWAN are introduced and the feasibility and the considerations of LoRaWAN-based star wireless sensor network are discussed. Secondly, an improved compressed sensing algorithm named ISL0 (improved SL0) is proposed for network data reconstruction and compressed sensing algorithm can reduce the number of LoRa nodes transmitting data packets to avoid collision and latency. Thirdly, a sleep schedule method is proposed to reliably monitor environment data and device operating status. By using the proposed method, not only the abnormal information can be detected on time, but also the overall network data can be recorded termly. Simulation and measurement results verify all nodes have same power level at different times, and the network lifetime is maximized.

With the greater availability and reduced dimensions of complex electronics, an Internet of Things (IoT) will emerge in the future, in which machines use sensors to collect and evaluate information about the physical world and share it with other machines without having to rely on human interaction. Blockchain technology encompasses features such as trustworthiness and decentralization and these features can be advantageous in the IoT context, as they can help to ensure data integrity in an Internet of Things unmonitored by humans. In the course of this paper, we investigate to what extent the use of blockchain technology is feasible for autonomous devices in IoT. For this purpose, a prototypical client blockchain component is built using the single-board computer Raspberry Pi and a simulated Ethereum blockchain. This prototype will be examined for aspects like proper functionality, response times and performance.

The long-range wide area network (LoRaWAN) has recently emerged as one of the most potential technologies for the mobile Internet of Things (IoT) applications. In a LoRaWAN, the network-managed adaptive data rate (ADR) method is responsible for managing resource allocation (i.e., spreading factor (SF) and transmit power (TP)) to end-devices (EDs) through ADR commands. When an ED is mobile and receives a new configuration (i.e., SF and TP) from the network server, the propagation scenario could have been dramatically changed. Hence, the SF and the link budget will no longer be valid, which results in packet loss and massive retransmissions. Therefore, we propose a mobility-aware resource (SF) assignment scheme (M-ASFA), which aims to allocate the best SF to IoT-enabled mobile EDs at each uplink transmission by considering the strength of the signals that a gateway receives from the EDs. The simulation results demonstrate that, in our proposed M-ASFA solution, the SF is assigned to mobile EDs by proactively responding to the mobility of the EDs. This proactive behavior of the proposed scheme enhances the packet success ratio by significantly reducing the impact of interference, retransmissions, and packet loss when compared with the LoRaWAN-based ADR.

This paper focuses on the comparison of transmission performances within critical environments (i.e., underwater, within metal enclosures and underground) for two of the most adopted enabling technologies for the Internet of Things (IoT): the Long Range Wide Area Network (LoRaWAN) protocol and the Narrowband Internet of Things (NB-IoT) standard. After a literature review, the two technologies are surveyed and compared. Then, the most exploited path loss models for the aforesaid application scenarios are presented. In order to assess and compare performances, a multi-protocol wireless sensor node prototype exploiting both the technologies for transmitting is described. Such prototype is then employed within field tests which consisted of underwater, through-metal and underground broadcasts with the aim of measuring losses only ascribed to the media. Eventually, tests results are analyzed and compared with the theoretical models.

Long-range wide-area network (LoRaWAN) is an energy-efficient and inexpensive networking technology that is rapidly being adopted for many Internet-of-Things applications. In this study, we perform extensive measurements on a new LoRaWAN deployment to characterise the spatio-temporal properties of the LoRaWAN channel. Our experiments reveal that LoRaWAN frames are mostly lost due to the channel effects, which are adverse when the end-devices are mobile. The frame losses are up to 70 percent, which can be bursty for both mobile and stationary scenarios. Frame losses result in data losses since the frames are transmitted only once in the basic configuration. To reduce data losses in LoRaWAN, we design a novel coding scheme for data recovery called DaRe that works on the application layer. DaRe combines techniques from convolutional and fountain codes. By implementing DaRe, we show that 99 percent of the data can be recovered with a code rate of 1/2 when the frame loss is up to 40 percent. Compared to the repetition coding scheme, DaRe provides 21 percent higher data recovery and can save up to 42 percent of the energy consumed on a transmission for 10-byte data units. We also show that DaRe provides better resilience to bursty frame losses.

Motivation. After the Fukushima, nuclear power plant (NPP) accident, an unmanned aerial vehicle (UAV)-enabled wireless network (UEWN) is considered to be used for transmitting the data from monitoring stations (MSs) to the crisis center (CrS) during NPP post-accident monitoring missions. Nevertheless, the popular lightweight UAVs have an endurance of about 20–40 minutes only. The last fact presents a significant barrier to use a UEWN in complex, long-term NPP post-accident monitoring missions. The subject matter of the paper is the process of ensuring the persistent operation of UEWN. This paper aims to propose an approach to ensuring the persistent operation of UEWN during NPP post-accident monitoring missions via automatic battery replacement stations (ABRSs). The objectives of the paper are: to propose a scheme of deployment of a UEWN with ABRSs for the given scenario; to give an example of the proposed scheme application for persistent transmitting the data from a MS to the CrS during Zaporizhzhia NPP (ZNPP) post-accident monitoring missions; to discuss an example of the proposed scheme application. The following results were obtained. A simplified scheme of deployment of a UEWN with ABRSs for transmitting the data from the MS to the CrS during NPP post-accident monitoring missions was developed and described. Two segments within the UEWN were considered: 1) Wi-Fi segment, comprising the WiFi equipment of the MS, the onboard WiFi equipment of the UAVs of a multi-rotor type (MUAVs), and onboard WiFi equipment of the UAV of an airplane-type (AUAV); 2) LoRaWAN segment, comprising the LoRaWAN equipment of the AUAV and the LoRaWAN equipment of the CrS. An example of deployment of a UEWN with ABRSs for transmitting the data from an MS of ZNPP to the CrS was given and described. A shift schedule for 2 MUAV fleets ensuring the persistent operation of the UEWN during post-accident ZNPP monitoring missions was built and analyzed. It was evaluated how the flight distance for the MUAV between its location point in the WiFi segment and the ABRS effects: the duty time for the MUAV fleet; the waiting time for the MUAV to flight to the point of its location in the WiFi segment; the number of the MUAV fleets for ensuring the persistent operation of the UEWN. The new research will aim at developing a scheme of deployment of the UEWN with ABRSs for several WiFi segments

LoRaWAN deployments follow an ad-hoc deployment model that has organically led to overlapping communication networks, sharing the wireless spectrum, and completely unaware of each other. LoRaWAN uses ALOHA-style communication where it is almost impossible to schedule transmission between networks belonging to different owners properly. The inability to schedule overlapping networks will cause inter-network interference, which will increase node-to-gateway message losses and gateway-to-node acknowledgement failures. This problem is likely to get worse as the number of LoRaWAN networks increase. In response to this problem, we propose IRONWAN, a wireless overlay network that shares communication resources without modifications to underlying protocols. It utilises the broadcast nature of radio communication and enables gateway-to-gateway communication to facilitate the search for failed messages and transmit failed acknowledgements already received and cached in overlapping network's gateways. IRONWAN uses two novel algorithms, a Real-time Message Inter-arrival Predictor, to highlight when a server has not received an expected uplink message. The Interference Predictor ensures that extra gateway-to-gateway communication does not negatively impact communication bandwidth. We evaluate IRONWAN on a 1000-node simulator with up to ten gateways and a 10-node testbed with 2-gateways. Results show that IRONWAN can achieve up to 12\% higher packet delivery ratio (PDR) and total messages received per node while increasing the minimum PDR by up to 28\%. These improvements save up to 50\% node's energy. Finally, we demonstrate that IRONWAN has comparable performance to an optimal solution (wired, centralised) but with 2-32 times lower communication costs. IRONWAN also has up to 14\% better PDR when compared to FLIP, a wired-distributed gateway-to-gateway protocol in certain scenarios., Accepted for publication at IEEE Internet of Things Journal

The aim of this paper is to present the viability of an energy-harvesting system prototype, based on thermoelectric generators (TEGs), to be embedded in a Long-Range Wide Area Network (LoRaWAN)-based wireless sensor node, allowing continuous quasi-real-time data transmission even for low temperature gradients and for frequent transmissions. To this end, an RFM95x LoRa module is used in the system. The energy management of the entire node is achieved by exploiting a nano power boost charger buck converter integrated circuit, which allows power extraction from the energy-harvesting source and, at the same time, regulates the charging/discharging process of a Li-Po battery that supplies the wireless node. The first phase of the project was dedicated to understanding the electrical characteristics of the TEG. A series of tests were performed to study the open circuit voltage, the current and the power generated by the TEG at different temperature gradients. Following this first phase, tests were then set up to study the charging/discharging process of the battery by changing two crucial parameters: the temperature between the faces of the TEG and the frequency of the transmissions performed by the transceiver. Experimental results show a positive balance for the battery charging at different conditions, which suggests two important conclusions: first of all, with high temperature gradients, it is possible to set relatively high transmission frequencies for the LoRaWAN module without discharging the battery. The second important consideration concerns the operation of the system at extremely low temperature gradients, with a minimum of 5 °C reached during one of the measurements. This suggests the usability of thermoelectric energy-harvesting systems in a wide range of possible applications even in conditions of low temperature gradients.

The introduction of low-power wide-area networks (LPWANs) has changed the image of smart systems, due to their wide coverage and low-power characteristics. This category of communication technologies is the perfect candidate to be integrated into smart inverter control architectures for remote microgrid (MG) applications. LoRaWAN is one of the leading LPWAN technologies, with some appealing features such as ease of implementation and the possibility of creating private networks. This study is devoted to analyze and evaluate the aforementioned integration. Initially, the characteristics of different LPWAN technologies are introduced, followed by an in-depth analysis of LoRa and LoRaWAN. Next, the role of communication in MGs with widespread elements is explained. A point-by-point LoRa architecture is proposed to be implemented in the grid-feeding control structure of smart inverters. This architecture is experimentally evaluated in terms of latency analysis and externally generated power setpoint, following smart inverters in different LoRa settings. The results demonstrate the effectiveness of the proposed LoRa architecture, while the settings are optimally configured. Finally, a hybrid communication system is proposed that can be effectively implemented for remote residential MG management.

International audience; Interest and need for Wireless Body Area Networks (WBANs) havesignicantly increased recently. WBAN consists of miniaturized sensors de-signed to collect and transmit data through wireless network, enabling medicalspecialists to monitor patients during their normal daily life and providing realtime opinions for medical diagnosis. Many wireless technologies have provedthemselves in WBAN applications, while others are still under investigations.The choice of the technology to adopt may depend on the disease to moni-tor and the performance requirements, i.e. reliability, latency and data rate.In addition, the suitable sensor is essential when seeking to extract the datarelated to a medical measure.This paper aims at surveying the wireless technologies used in WBAN sys-tems. In addition to a detailed survey on the existing technologies, the use ofthe emerging Low Power Wide Area Network (LPWAN) technologies, and thefuture 5G, B5G and 6G is investigated, where the suitability of these technolo-gies to WBAN applications is studied from several perspectives. Furthermore,medical applications of WBAN are discussed by presenting their methodolo-gies, the adopted wireless technologies and the used sensors. Given that eachmedical application requires the appropriate sensor to extract the data, wehighlight a wide range of the sensors used in the market for medical systems.Recent and future challenges in WBAN systems are given related to the powerconsumption, the emergence of the Internet of Things (IoT) technologies inWBAN and others.

In this paper the idea of functioning of Building Management Systems and Object Management Systems in intelligent buildings is presented. New functionalities of intelligent buildings resulting from the introduction of microgeneration are described. Low-Power Wide-Area Networks (LPWAN) are characterized and compared. The selected Long-Range (LoRaWAN) technology is tested for its use for communication with energy meters and monitoring the power supply network in intelligent buildings. In the paper a new system for reading and monitoring the network is proposed, consisting of hardware, communication, and application layers. A key element of the system is a specially developed converter, which has been designed and tested in a real urban environment. Using our solution in practice could allow to change the architecture of a measurement data acquisition system to much more flexible and efficient.

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.

LoRaWAN has gained significant attention for Internet-of-Things (IOT) applications due to its low power consumption and long range potential for data transmission. While there is a significant body of work assessing LoRA coverage and data transmission characteristics, there is a lack of data available about commercially available LoRa prototyping boards and their power consumption, in relation to their features. It is currently difficult to estimate the power consumption of a LoRa module operating under different transmission profiles, due to a lack of manufacturer data available. In this study, power testing has been carried out on physical hardware and significant variation was found in the power consumption of competing boards, all marketed as “extremely low power”. In this paper, testing results are presented alongside an experimentally-derived power model for the lowest power LoRa module, and power requirements are compared to firmware settings. The power analysis adds to existing work showing trends in data-rate and transmission power settings effects on electrical power consumption. The model’s accuracy is experimentally verified and shows acceptable agreement to estimated values. Finally, applications for the model are presented by way of a hypothetical scenario and calculations performed in order to estimate battery life and energy consumption for varying data transmission intervals.

Irrigation installations in cities or agricultural operations use large amounts of water and electrical energy in their activity. Therefore, optimising these resources is essential nowadays. Wireless networks offer ideal support for such applications. The long-range wide-area network (LoRaWAN) used in this research offers a large coverage of up to 5 km, has low power consumption and does not need additional hardware such as repeaters or signal amplifiers. This research develops a control and monitoring system for irrigation systems. For this purpose, an irrigation algorithm is designed that uses rainfall probability data to regulate the irrigation of the installation. The algorithm is complemented by checking the sending and receiving of information in the LoRa network to reduce the loss of information packets. In addition, two temperature and humidity measurement devices for LoRaWAN (THMDLs) and an electrovalve control device for LoRaWAN (ECDLs) were developed. The hardware and software were also designed, and prototypes were built with the development of the electronic board. The wide coverage of the LoRaWAN allows the covering of small to large irrigation areas.

LoRa Wide Area Networks (LoRaWAN) can provide a connectivity service to Internet of Things (IoT) for an extremely long run-time and with low power consumption. As the LoRaWAN is extensively applied to various IoT scenarios, LoRaWAN solutions face a flexibility issue in terms of inter-operating with various kinds of LoRa modem hardware and protocol scenarios. In this regard, we design a unified protocol architecture for LoRaWAN physical layer, which can flexibly correspond to various deployment and operational cases. The new protocol architecture includes a hardware abstraction sub-layer, which contains generalized handlers for configuring various kinds of the LoRa modem, and a physical procedure sub-layer that structurally models the physical layer procedures of the LoRaWAN based on Finite State Machine(FSM). We illustrate the flexibility of the new protocol architecture by implementing an extensive feature that enhances the packet reception ratio based on the status of preamble detection. For evaluating the new protocol architecture, we implement the LoRaWAN physical layer protocol on real-time embedded systems and conduct experiments. The experimental results show that the proposed protocol robustly transmits and receives packets and generates little amount of additional burden compared with the conventional open source protocol provided by SemTech.

International audience; LoRa is one of the leading technologies for Low-Power Wide Area Networks and the Internet of Things. Collisions in LoRa might cause retransmissions, which negatively impact the network performance and scalability. Several algorithms have been proposed to decode colliding frames under specific conditions. However, there remain indistinguishable frames due to uncertainties in some or all symbols. In this paper, we propose a general algorithm that significantly improves the recovery capabilities of existing algorithms by leveraging the LoRa coding techniques. Simulation results show that our algorithm can significantly reduce the number of the failed decoding of LoRa frames and improve the performance of the network.

Accurate localization for wireless sensor end devices is critical, particularly for Internet of Things (IoT) location-based applications such as remote healthcare, where there is a need for quick response to emergency or maintenance services. Global Positioning Systems (GPS) are widely known for outdoor localization services, however, high-power consumption and hardware cost become a significant hindrance to dense wireless sensor networks in large-scale urban areas. Therefore, wireless technologies such as Long-Range Wide-Area Networks (LoRaWAN) are being investigated in different location-aware IoT applications due to having more advantages with low-cost, long-range, and low-power characteristics. Furthermore, various localization methods, including fingerprint localization techniques, are present in the literature but with different limitations. This study uses LoRaWAN Received Signal Strength Indicator (RSSI) values to predict the unknown X and Y position coordinates on a publicly available LoRaWAN dataset for Antwerp in Belgium using Random Neural Networks (RNN). The proposed localization system achieves an improved high-level accuracy for outdoor dense urban areas and outperforms the present conventional LoRa-based localization systems in other work, with a minimum mean localization error of 0.29 m.

Seeking to solve problems in the power electric system (PES) related to exacerbated and uncontrolled energy consumption by final consumers such as residences, condominiums, public buildings and industries, electric power companies (EPC) are increasingly seeking new information and communication technologies (ICTs) to transform traditional electric power distribution networks into smart grids (SG). With this implementation, PES will be able to remotely control electric power consumption as well as monitor data generated by smart meters (SM). However, Internet-of-Things (IoT) technologies will enable all this to happen quickly and at low cost, since they are low-cost devices that can be deployed quickly and at scale in these scenarios. With this in mind, this work aimed to study, propose, and implement a hybrid communication infrastructure with LoRaWAN and LoraMesh for the demand-side management as a service (HyDSMaaS) using IoT devices such as long range (LoRa) to provide an advanced metering infrastructure (AMI) capable of performing all these applications as a service offered by EPC to end consumers. Additionally, services such as demand-side management (DSMaaS) can be used in this infrastructure. From the preliminary results it was found that the LoRaWAN network achieved a range of up to 2.35 km distance and the LoRaMESH one of 600 m, thus, the latter is more suitable for scenarios where there is little interference and the SMs are at long distances, while the other is used for scenarios with greater agglomeration of nearby SMs. Considering the hybridized scenario between LoraWAN and LoRaMESH, it can be seen that the implementation possibilities increase, since its range was approximately 3 km considering only one hop, and it can reach 1023 devices present in a mesh network. Thus, it was possible to propose the actual implementation of LoRaWAN and LoRaMESH protocols as well as the hybridization of the two protocols for HyDSMaaS. Additionally, the results obtained are exclusively from Radioenge’s LoRa technology, which can be further improved in the case of using more powerful equipment.

© 2021 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) LoRaWAN has become a popular technology for the Internet of Things (IoT) device connectivity. One of the expected properties of LoRaWAN is high network scalability. However, LoRaWAN network performance may be compromised when even a relatively small number of devices use link-layer reliability. After failed frame delivery, such devices typically tend to reduce their physical layer bit rate by increasing their spreading factor (SF). This reaction increases channel utilization, which may further degrade network performance, even into congestion collapse. When this problem arises, all the devices performing reliable frame transmission end up using SF12 (i.e., the highest SF in LoRaWAN). In this paper, we identify and characterize the described network condition, which we call the SF12 Well, in a range of scenarios and by means of extensive simulations. The results show that by using alternative SF-management techniques it is possible to avoid the problem, while achieving a packet delivery ratio increase of up to a factor of 4.7.

Most Internet of Things (IoT) communication technologies rely on terrestrial network infrastructure. When such infrastructure is not available or does not provide sufficient coverage, satellite communication offers an alternative IoT connectivity solution. Satellite-enabled IoT devices are typically powered by a limited energy source. However, as of this writing, and to our best knowledge, the energy performance of satellite IoT technology has not been investigated. In this paper, we model and evaluate the energy performance of Iridium satellite technology for IoT devices. Our work is based on real hardware measurements. We provide average current consumption, device lifetime, and energy cost of data delivery results as a function of different parameters. Results show, among others, that an Iridium-enabled IoT device, running on a 2400 mAh battery and sending a 100-byte message every 100 min, may achieve a lifetime of 0.95 years. However, Iridium device energy performance decreases significantly with message rate. This work was supported in part by the Spanish Government through project PID2019- 106808RA-I00, AEI/FEDER, EU, and by Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya through project 2017 SGR 376.

A Long-Range Wide Area Network (LoRaWAN) is one of the most efficient technologies and is widely adopted for the Internet of Things (IoT) applications. The IoT consists of massive End Devices (EDs) deployed over large geographical areas, forming a large environment. LoRaWAN uses an Adaptive Data Rate (ADR), targeting static EDs. However, the ADR is affected when the channel conditions between ED and Gateway (GW) are unstable due to shadowing, fading, and mobility. Such a condition causes massive packet loss, which increases the convergence time of the ADR. Therefore, we address the convergence time issue and propose a novel ADR at the network side to lower packet losses. The proposed ADR is evaluated through extensive simulation. The results show an enhanced convergence time compared to the state-of-the-art ADR method by reducing the packet losses and retransmission under dynamic mobile LoRaWAN network.

The remarkable evolution of the IoT raised the need for an efficient way to update the device’s firmware. Recently, a new process was released summarizing the steps for firmware updates over the air (FUOTA) on top of the LoRaWAN protocol. The FUOTA process needs to be completed quickly to reduce the systems’ interruption and, at the same time, to update the maximum number of devices with the lowest power consumption. However, as the literature showed, a single gateway cannot optimize the FUOTA procedure and offer the above mentioned goals since various trade-offs arise. In this paper, we conducted extensive experiments via simulation to investigate the impact of multiple gateways during the firmware update process. To achieve that, we extended the FUOTAsim simulation tool to support multiple gateways. The results revealed that several gateways could eliminate the trade-offs that appeared using a single gateway

The massive deployment of Internet of Things (IoT) architectures and applications, in many fields over the last decade, has accelerated research efforts on low-power wireless connectivity protocols. Moreover, many standards have been introduced, highlighting the need to make data flow among different communication protocols and network interfaces feasible. To this end, devices like Gateways (GWs) play a crucial role in many IoT applications and will impact future developments and possibilities. In this paper, the design and deployment of a new modular and scalable GW architecture solution, suitable for a wide plethora of use case scenarios and useful as a starting point for many possible improvements and applications, is proposed. Experimental performance results are discussed, showing the roles of different interfaces in specific use cases in which the proposed this solution may be applied.

[EN] The adoption of LoRaWAN as a technology for wireless deployments in many applications, such as smart cities or industry 4.0, still presents challenges such as energy consumption, robustness, or reduced throughput in harsh, noisy scenarios. Class B is a MAC mode that allows better performance in downlink traffic but has difficulties regarding scalability and its response to channel interference. This article introduces, via simulation software, the possibility of testing deployments, adding interference sources that model industrial scenarios, and proposes an adaptive data rate (ADR) mechanism to enhance the operation for downlink and class B devices, called DROB (downlink rate optimization for class B) to study the impact of these conditions in a network with detailed event characterization., The research leading to these results received funding from the Horizon 2020 Program of the European Commission under Grant Agreement No. 825631 "Zero Defect Manufacturing Platform (ZDMP)". It was also partially supported by the MCyU (Spanish Ministry of Science and Universities) under the project ATLAS (PGC2018-094151-B-I00).

This paper proposes a novel network architecture integrating a multi-hop Long Range (LoRa)-based thin linear network within a LoRa Wide Area Network (LoRaWAN) infrastructure, with the aim of proposing linear distributed measurement systems forwarding their collected data to a LoRaWAN server by means of a hybrid LoRa-LoRaWAN node. Such device is able to collect LoRa packets coming from the linear network and to encapsulate them in LoRaWAN packets transmitted to the remote server by means of standard LoRaWAN Gateways. The operation of the nodes is regulated by an ad-hoc routing protocol which aims at minimizing their active period, in order to reduce their power consumption increasing the overall system lifetime. Similarly, the synchronization of the nodes aims at increasing the robustness of the network reducing at minimum packet losses. The effectiveness of the proposed network architecture in terms of successful packet deliveries and reduction of active time is tested in different configurations, exploiting 2-node, 3-node and 4-node chains as well as adopting increasingly larger cycle periods. Results show that the proposed configuration ensures a noteworthy robustness in terms of packets delivery while maintaining the duty-cycling at levels that may guarantee long life times and autonomous operation to the overall infrastructure.

The penetration of wearable devices in our daily lives is unstoppable. Although they are very popular, so far, these elements provide a limited range of services that are mostly focused on monitoring tasks such as fitness, activity, or health tracking. Besides, given their hardware and power constraints, wearable units are dependent on a master device, e.g., a smartphone, to make decisions or send the collected data to the cloud. However, a new wave of both communication and artificial intelligence (AI)-based technologies fuels the evolution of wearables to an upper level. Concretely, they are the low-power wide-area network (LPWAN) and tiny machine-learning (TinyML) technologies. This paper reviews and discusses these solutions, and explores the major implications and challenges of this technological transformation. Finally, the results of an experimental study are presented, analyzing (i) the long-range connectivity gained by a wearable device in a university campus scenario, thanks to the integration of LPWAN communications, and (ii) how complex the intelligence embedded in this wearable unit can be. This study shows the interesting characteristics brought by these state-of-the-art paradigms, concluding that a wide variety of novel services and applications will be supported by the next generation of wearables.

International audience; Long Range Wide Area Network (LoRaWAN) introduces the Adaptive Data rate (ADR) mechanism [1] aiming to maximize both battery life of the end-devices and overall network capacity. ADR performs adaptive tuning of radio configurations of the nodes by adjusting bandwidth, spreading factor, coding rate and transmission power parameters whenever the signal quality changes. The ADR algorithm was established for stable radio channel environments and is not efficient when conditions dramatically change (e.g. mobility). So, we have previously proposed an Enhanced-ADR (E-ADR) [2] that deals mobile nodes in case of predefined mobility patterns. However, several Internet Of Thing (IoT) applications, such as smart cattle ranching in smart farms [3], require sensors travelling with unknown or undefined trajectories. So, this paper extends E-ADR to unknown mobility pattern. This E-ADR extension, called VHMM-based E-ADR, is based on a Variable order Hidden Markov Model (VHMM) to predict the node trajectory. It has been implemented on Waspmote SX1272 hardware platform. Experimental results show its high efficiency in terms of the packet loss rate (PLR) and the energy consumption.

International audience; The growing need for localization has created an array of alternative approaches to GNSS, based on Wi-Fi, Bluetooth, Ultra-Wideband, etc. Long Range Wide Area Network (LoRaWAN) is one such technology that has garnered tremendous attention due to its low power and long-range capabilities. Many attempts to achieve localization using LoRaWAN have been made till now, based on a variety of techniques such as Angle of Arrival (AoA), Time Difference of Arrival (TDoA), Received Signal Strength Index (RSSI). In this paper, we present a novel, standalone localization approach by developing a collaborative, TDoA-based methodology using LoRaWAN. The server determines the target node location by means of TDoA measurements from the target node to the gateways. The introduction of an additional stationary node allows the synchronization of the gateways without utilizing GNSS, either inbuilt or external. The cooperation between target node, synchronization node and server, is the innovative feature which makes this approach attractive for GNSS-free localization. Further, we explore the effects of timing resolution, time-on-air, and duty cycle constraints on the localization error. Finally, the distribution of error in a triangle of gateways situated approximately 8.6 kilometers apart is simulated in ideal Line of Sight (LoS) conditions, showing the maximum error to be around 23 meters.

Low-power wide-area networks are continuously gaining momentum as enablers of massive machine-type communication, thanks to long-range wireless technologies operating either on unlicensed spectrum like, e.g., Long-Range (LoRa) and Sigfox, or on licensed spectrum, as Narrowband-IoT. For the former category of technologies, stringent requirements in terms of channel utilization and radiated power must be fulfilled, thus algorithms and protocols for enhanced radio-resource management need to be investigated. In this paper, we propose a disruptive approach for LoRa systems, exploiting a novel operational mode at the gateways side called time-power multiplexing, which fully exploits the degrees of freedom of the unlicensed bands regulations. The simulation results show that the proposed solution boosts the number of users that a LoRa network can support with respect to the default operational mode.