Survey on wireless technology trade-offs for the industrial internet of things

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

A neural network propagation model for LoRaWAN and critical analysis with real-world measurements

Among the many technologies competing for the Internet of Things (IoT), one of the most promising and fast-growing technologies in this landscape is the Low-Power Wide-Area Network (LPWAN). Coverage of LoRa, one of the main IoT LPWAN technologies, has previously been studied for outdoor environments. However, this article focuses on end-to-end propagation in an outdoor–indoor scenario. This article will investigate how the reported and documented outdoor metrics are interpreted for an indoor environment. Furthermore, to facilitate network planning and coverage prediction, a novel hybrid propagation estimation method has been developed and examined. This hybrid model is comprised of an artificial neural network (ANN) and an optimized Multi-Wall Model (MWM). Subsequently, real-world measurements were collected and compared against different propagation models. For benchmarking, log-distance and COST231 models were used due to their simplicity. It was observed and concluded that: (a) the propagation of the LoRa Wide-Area Network (LoRaWAN) is limited to a much shorter range in this investigated environment compared with outdoor reports; (b) log-distance and COST231 models do not yield an accurate estimate of propagation characteristics for outdoor–indoor scenarios; (c) this lack of accuracy can be addressed by adjusting the COST231 model, to account for the outdoor propagation; (d) a feedforward neural network combined with a COST231 model improves the accuracy of the predictions. This work demonstrates practical results and provides an insight into the LoRaWAN’s propagation in similar scenarios. This could facilitate network planning for outdoor–indoor environments

An IoT Measurement System Based on LoRaWAN for Additive Manufacturing

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible

Advanced IoT Technology and Protocols: Review and Future Perspectives

The Internet of Things (IoT) has emerged as a disruptive paradigm, altering how we interact with our surroundings and enabling a plethora of novel applications across multiple sectors. This literature review provides a complete overview of the Internet of Things, including applications, technology, protocols, modeling tools, and future directions. The assessment begins by looking at a wide range of IoT applications, such as smart cities, healthcare, industrial automation, smart homes, and more. It then looks into the underlying technologies that enable IoT deployments, including low-power wireless communication protocols, edge computing, and sensor networks. Protocols and routing methods designed expressly for IoT networks are also described, as well as simulation tools used to simulate and evaluate IoT systems. The discussion focuses on critical insights and consequences for the future of IoT, including challenges and potential in security, interoperability, edge intelligence, and sustainability. By tackling these obstacles and using emerging technologies, IoT can create disruptive change across businesses while also improving quality of life. This review seeks to give scholars, practitioners, and stakeholders a thorough grasp of IoT and its implications for the future

Energy efficiency in LoRaWAN

Abstract. Low-power wide-area networks (LPWANs) are emerging rapidly as a fundamental Internet of Things (IoT) technology because of features like low-power consumption, long-range connectivity, and the ability to support massive numbers of users. With its high growth rate, Long Range (LoRa) is becoming the most adopted LPWAN technology. Sensor nodes are typically powered by batteries, and many network applications, which expect end-devices to operate reliably for a prolonged time. Each sensor node or actuator consumes a distinct current for a different period of time, depending on its operational state. To model a self-sufficient sensor nodes network, it is of the utmost importance to investigate the energy consumption of class-A end-devices in a LoRa Wide Area Network (LoRaWAN) with the impact of respective physical and MAC layers. Several latest published research works have analyzed the energy consumption model of a sensor node in different transmission (confirmed or unconfirmed) modes and also examined the network performance of LoRaWAN under uplink outage probabilities. This research work investigates the energy cost of the LoRaWAN, deploying hundreds of sensor nodes to transmit information messages. The proposed scheme is evaluated by considering the average power consumption of end-device powered by 2400 mAh battery. Furthermore, the energy efficiency of an unconfirmed transmission network is examined to provide the optimal number of sensor nodes for each spreading factor

Smart city pilot projects using LoRa and IEEE802.15.4 technologies

Information and Communication Technologies (ICTs), through wireless communications and the Internet of Things (IoT) paradigm, are the enabling keys for transforming traditional cities into smart cities, since they provide the core infrastructure behind public utilities and services. However, to be effective, IoT-based services could require different technologies and network topologies, even when addressing the same urban scenario. In this paper, we highlight this aspect and present two smart city testbeds developed in Italy. The first one concerns a smart infrastructure for public lighting and relies on a heterogeneous network using the IEEE 802.15.4 short-range communication technology, whereas the second one addresses smart-building applications and is based on the LoRa low-rate, long-range communication technology. The smart lighting scenario is discussed providing the technical details and the economic benefits of a large-scale (around 3000 light poles) flexible and modular implementation of a public lighting infrastructure, while the smart-building testbed is investigated, through measurement campaigns and simulations, assessing the coverage and the performance of the LoRa technology in a real urban scenario. Results show that a proper parameter setting is needed to cover large urban areas while maintaining the airtime sufficiently low to keep packet losses at satisfactory levels

LoRa Enabled Smart Inverters for Microgrid Scenarios with Widespread Elements

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

Experimental Characterization of LoRaWAN Link Quality

International audienceIn this paper, we present the results of extensive experiments on a testbed in the The Things Network (TTN), a public LoRa network. We evaluate the transmission quality of LoRa links by measuring the Packet Reception Rate (PRR) as a function of the payload length. The results show that there is only a slight impact of the payload length on PRR, which means that the bit error rate does not strongly influence the probability of packet reception. Our measurements show that the LoRa channel behaves like a slow fading Rayleigh channel, which translates into probability Ps of being (or not) in a favorable condition for each frame reception: once the frame preamble is received, there is great chance that the whole frame is correctly received. Probability Ps depends on the Spreading Factor and the Signal to Noise Ratio, and often becomes a dominant factor of successful reception depending on the signal strength at a gateway