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Many new narrowband low-power wide-area networks (LPWANs) (e.g., LoRaWAN, Sigfox) have opted to use pure ALOHA-like access for its reduced control overhead and asynchronous transmissions. Although asynchronous access reduces the energy consumption of IoT devices, the network performance suffers from high intra-network interference in dense deployments. Contrarily, adopting synchronous access can improve throughput and fairness, however, it requires time synchronization. Unfortunately, maintaining synchronization over the narrowband LPWANs wastes channel time and transmission opportunities. In this paper, we propose the use of out-of-band time-dissemination to relatively synchronize the LoRa devices and thereby facilitate resource-efficient slotted uplink communication. In this respect, we conceptualize and analyze a co-designed synchronization and random access communication mechanism that can effectively exploit technologies providing limited time accuracy, such as FM radio data system (FM-RDS). While considering the LoRa-specific parameters, we derive the throughput of the proposed mechanism, compare it to a generic synchronous random access using in-band synchronization, and design the communication parameters under time uncertainty. We scrutinize the transmission time uncertainty of a device by introducing a clock error model that accounts for the errors in the synchronization source, local clock, propagation delay, and transceiver’s transmission time uncertainty. We characterize the time uncertainty of FM-RDS with hardware measurements and perform simulations to evaluate the proposed solution. The results, presented in terms of success probability, throughput, and fairness for a single-cell scenario, suggest that FM-RDS, despite its poor absolute synchronization, can be used effectively to realize time-slotted communication in LoRa with performance similar to that of more accurate time-dissemination technologies.

The monitoring of pollutants in industrial plants is a major concern, in order to satisfy the requirements dictated by the related norms. Recently, the problem of odor monitoring gained importance since, despite the generally low dangerous nature of the emission, people usually correlate bad smell to unhealthy air condition. In this paper, we focus on the wastewater treatment application scenario and propose a versatile air pollution control solution. In particular, a distributed eNose, based on low-cost, but highly configurable sensing probes, is suggested. The Internet of Things (IoT) paradigm has been followed, thanks to the adoption of a communication infrastructure based on the widely adopted LoRaWAN technology. Such an approach, on one hand, would allow to easily cope with the administration and local population; on the other hand, it paves the way to use analytics to predict emission events in advance. The need for managing multiple transducers per each probe has been solved using an innovative acquisition strategy, exploiting both the volt-amperometric and resistance-to-time (integral) approaches, implemented by low-cost microcontroller and ancillary electronics. A proof-of-concept prototype has been realized and preliminary experiments have been carried out. Experimental results have demonstrated the solidity of the proposed approach, with relative error below 1% and relative standard deviation below 0.5% over the whole considered resistive range of more than two decades. © 2021 IEEE.

Differential capacitive sensors, especially if implemented as MEMS (Micro Electro Mechanical Systems) are a widely employed sensor solution, especially after the widespread adoption of the IoT (Internet of things) paradigm. These sensors target very different applications, including accelerometers, gyroscopes, barometers, just to mention a few, because they can take advantage from lower power consumption, better temperature coefficient and manufacturability. The readout circuit plays a central and fundamental role in ensuring optimal overall performance. In this paper, a frontend for interfacing differential capacitive sensors with microcontroller-based systems is discussed and performance is evaluated. In particular, the use of voltage mode is considered and, consequently, the stray capacitance can deeply affect the readouts. The proposed interface evaluates the mismatch between the current flowing in the two sensor equivalent capacitors and estimates the parasitic value. Additionally, the information about the current unbalance is used to improve the measurand estimation. In particular, the proposed approach is able to decrease of one order of magnitude the measurand estimation error, when large stray capacitance affects the sensor. © 2021 IEEE., Export Date: 20 September 2021; Conference Paper; CODEN: CRIIE

Industry 4.0 paradigm improves industrial automation systems efficiency leveraging on the Industrial Internet of Things (IIoT), offering pervasive connectivity with field devices and paving the way to innovative services. Updating legacy machines in brownfield installations is needed for preserving investments. This paper discusses the design and the experimental validation in a real-world use case of a low-cost solution aiming at providing LoRaWAN Class A connectivity to a Programmable Logic Controller (PLC). Widespread modules, offering full compatibility with the standard, are considered. They behave as 'modems' controlled by AT-like commands via simple serial links (RS232), minimizing the need for additional glue logic. The developed solution has been connected to a public LoRaWAN infrastructure, showing average uplink delays in the order of 300-500 ms; on the contrary, downlink messages are constrained by uplink interarrival time. The experiments also highlighted strong correlation between the LoRaWAN network congestion and the end-to-end delay. © 2021 IEEE., Export Date: 20 September 2021; Conference Paper

The advent of the Internet of Things (IoT) paradigm highlighted the importance of core technologies at the root of any distributed systems, as wireless communications, cloud computing and big data analysis. Today, companies and organizations, pursuing the so-called Industry 4.0 (r)evolution, are moving toward smart factories, smart workforce, and intelligent transportation. The use of IoT technologies for connecting smart vehicles is identified by the IoV acronym, i.e. the Internet of Vehicle. In this work, the authors address the characterization of a distributed measurement platform for vehicle fleet management, focusing on time-related performance. In particular, a commercially available solution has been considered and real-world use cases have been identified, showing obtainable performance: with default configuration, an average overall delay less than 11 s has been estimated. © 2021 IEEE., Export Date: 20 September 2021; Conference Paper; CODEN: CRIIE

In this article, industrial control systems include networked control systems (NCS), which use real-time Ethernet (RTE) protocols since many years, well before the time sensitive networking initiative debut. Today, ethernet-based control systems are used all across Industry 4.0, including in critical applications, allowing for straight integration with information technology layers. Even if it is known that current RTE protocols do not have strong authentication or ciphering options, it is still very challenging to perform undetected cyber-attacks to these protocols while the NSC is in operation, in particular because such attacks must comply with very strict and small temporal constraints. In this article, a model-based attack is proposed for service degradation of NCS. The attack is carried out in real-time and it can remain undetected for the entire plant life. The attack can be applied to any RTE protocols and, without loss of generality, a detailed analysis of stealth techniques is provided for a specific real use case based on PROFINET. The experimental results demonstrate the feasibility of the proposed attack and its high effectiveness. The article also points out some possible future investigation directions in order to mitigate the attack. © 1982-2012 IEEE., Cited By :1; Export Date: 20 September 2021; Article; CODEN: ITIED; Correspondence Address: Ferrari, P.; Department of Information Engineering, Italy; email: paolo.ferrari@unibs.it

Low Power Wide Area Networks (LPWANs) are wireless technologies well accepted in the Internet of Things (IoT) scenarios because they operate in both public and private infrastructure using unlicensed frequency bands. Differently from other wireless standards, the LPWAN target applications are low-rate, sporadic-transmission, low-energy systems. Surely, fast response time and high reliable communication are out of the original LPWAN scope. In this work, a first investigation about the use LoRaWAN (one the most diffused LPWAN protocols) for notification of emergency messages across industrial plants is reported. The opportunity of using recently proposed low-cost repeaters, and the creation of a clever replication pattern of radio messages are the keys of the proposed approach. The results of the preliminary analytical feasibility assessment are presented, confirming the possibility to increase success ratio of notification and respective confirmation in case of emergencies. © 2021 IEEE., Export Date: 20 September 2021; Conference Paper

As the number of installed Battery Energy Storage Systems (BESSs) increases, the concerns related to possible cyberattacks to these systems rise accordingly. The most of BESS owners knows their systems may be vulnerable, but they often consider only denial of service attacks in their risk assessment. Unfortunately, other, subtler and more dangerous attacks exist. In this paper we show that a stealth attack to BESSs can be performed by applying a Man-in-the-Middle (MitM) approach. The aim of the attack is to stealthily manage the physical system by hiding the actual behavior of the system to its supervisory controller. In this case the attacker would be able to: (i) degrade the BESS by reducing its expected lifetime, (ii) produce economic losses for the prosumer, and (iii) affect the security and stability of the grid. The feasibility of the attack is demonstrated by providing an example of a stealth MitM attack on a real BESS coupled with a photovoltaic power plant. The proposed case study demonstrates that such attack can be performed without being discovered by end-users and shows that its effects can be severe. Finally, possible strategies to avoid or detect such kind of attack are discussed. IEEE, Export Date: 20 September 2021; Article

The spreading of IoT in every applications triggered the creation of many IoT frameworks. Many of them are compatible with several transmission protocols to collect data from IoT end-nodes (e.g. sensors/actuators). This paper introduces a new approach for the management of multi-protocol IoT architecture with redundancy features. Assuming the functional view diagram of IoT Architecture reference project (IoT-A), adaptations in communication and management functional blocks have been introduced to support redundancy based on multi-protocol and all the related management issues. The main goal is to keep this feature transparent for the rest of the system, which includes the application and its users. An experimental setup was designed and experiments were carried out to demonstrate feasibility and to characterize performance of the proposed solution. The results show that, with the multi-protocol redundancy activated, the IoT framework is capable of transparently delivering more information to the user application. © 2021 IEEE., Export Date: 20 September 2021; Conference Paper; Correspondence Address: Silva, D.R.C.; Science and Technology School, Brazil; email: diego@ect.ufrn.br; Correspondence Address: Cunha, R.N.; Science and Technology School, Brazil; email: rafael.cunha.035@ufrn.edu.br

Wireless technologies play a key role in the Industrial Internet of Things (IIoT) scenario, for the development of increasingly flexible and interconnected factory systems. A significant opportunity in this context is represented by the advent of Low Power Wide Area Network (LPWAN) wireless technologies, that enable a reliable, secure, and effective transmission of measurement data over long communication ranges and with very low power consumption. Nevertheless, reliability in harsh environments (as typically occurs in the industrial scenario) is a significant issue to deal with. Focusing on LoRaWAN, adaptive strategies can be profitably devised concerning the above tradeoff. To this aim, this paper proposes to exploit Reinforcement Learning (RL) techniques to design an adaptive LoRaWAN strategy for industrial applications. The RL is spreading in many fields since it allows the design of intelligent systems using a stochastic discrete-time system approach. The proposed technique has been implemented within a purposely designed simulator, allowing to draw a preliminary performance assessment in a real-world scenario. A high density of independent nodes per square km has been considered, showing a significant improvement (about 10%) of the overall reliability in terms of data extraction rate (DER) without compromising full compatibility with the standard specifications. © 2021 IEEE., Export Date: 20 September 2021; Conference Paper

Currently, the applications of the Internet of Things (IoT) generate a large amount of sensor data at a very high pace, making it a challenge to collect and store the data. This scenario brings about the need for effective data compression algorithms to make the data manageable among tiny and battery-powered devices and, more importantly, shareable across the network. Additionally, considering that, very often, wireless communications (e.g., low-power wide-area networks) are adopted to connect field devices, user payload compression can also provide benefits derived from better spectrum usage, which in turn can result in advantages for high-density application scenarios. As a result of this increase in the number of connected devices, a new concept has emerged, called TinyML. It enables the use of machine learning on tiny, computationally restrained devices. This allows intelligent devices to analyze and interpret data locally and in real time. Therefore, this work presents a new data compression solution (algorithm) for the IoT that leverages the TinyML perspective. The new approach is called the Tiny Anomaly Compressor (TAC) and is based on data eccentricity. TAC does not require previously established mathematical models or any assumptions about the underlying data distribution. In order to test the effectiveness of the proposed solution and validate it, a comparative analysis was performed on two real-world datasets with two other algorithms from the literature (namely Swing Door Trending (SDT) and the Discrete Cosine Transform (DCT)). It was found that the TAC algorithm showed promising results, achieving a maximum compression rate of 98.33%. Additionally, it also surpassed the two other models regarding the compression error and peak signal-to-noise ratio in all cases. © 2021 by the authors. Licensee MDPI, Basel, Switzerland., Export Date: 20 September 2021; Article; Correspondence Address: Silva, M.; UFRN-PPgEEC, Brazil; email: marianne.silva.086@ufrn.edu.br; Correspondence Address: Silva, I.; UFRN-PPgEEC, Brazil; email: ivanovitch.silva@ufrn.br

The technical innovation of the fourth industrial revolution (Industry 4.0—I4.0) is based on the following respective conditions: horizontal and vertical integration of manufacturing systems, decentralization of computing resources and continuous digital engineering throughout the product life cycle. The reference architecture model for Industry 4.0 (RAMI 4.0) is a common model for systematizing, structuring and mapping the complex relationships and functionalities required in I4.0 applications. Despite its adoption in I4.0 projects, RAMI 4.0 is an abstract model, not an implementation guide, which hinders its current adoption and full deployment. As a result, many papers have recently studied the interactions required among the elements distributed along the three axes of RAMI 4.0 to develop a solution compatible with the model. This paper investigates RAMI 4.0 and describes our proposal for the development of an open‐source control device for I4.0 applications. The control device is one of the elements in the hierarchy‐level axis of RAMI 4.0. Its main contribution is the integration of open‐source solutions of hardware, software, communication and programming, covering the relationships among three layers of RAMI 4.0 (assets, integration and communication). The implementation of a proof of concept of the control device is discussed. Experiments in an I4.0 scenario were used to validate the operation of the control device and demonstrated its effectiveness and robustness without interruption, failure or communication problems during the experiments. © 2021 by the authors. Licensee MDPI, Basel, Switzerland., Cited By :1; Export Date: 20 September 2021; Article; Correspondence Address: Godoy, E.P.; Department of Control and Automation Engineering, Brazil; email: eduardo.godoy@unesp.br

Although the idea of using wireless links for covering large areas is not new, the advent of Low Power Wide area networks (LPWANs) has recently started changing the game. Simple, robust, narrowband modulation schemes permit the implementation of low-cost radio devices offering high receiver sensitivity, thus improving the overall link budget. The several technologies belonging to the LPWAN family, including the well-known LoRaWAN solution, provide a cost-effective answer to many Internet-of-things (IoT) applications, requiring wireless communication capable of supporting large networks of many devices (e.g., smart metering). Generally, the adopted medium access control (MAC) strategy is based on pure ALOHA, which, among other things, allows to minimize the traffic overhead under constrained duty cycle limitations of the unlicensed bands. Unfortunately, ALOHA suffers from poor scalability, rapidly collapsing in dense networks. This work investigates the design of an improved LoRaWAN MAC scheme based on slotted ALOHA. In particular, the required time dissemination is provided by out-of-band communications leveraging on Radio Data System(FM-RDS) broadcasting, which natively covers wide areas both indoor and outdoor. An experimental setup based on low-cost hardware is used to characterize the obtainable synchronization performance and derive a timing error model. Consequently, improvements in success probability and energy efficiency have been validated by means of simulations in very large networks with up to 10000 nodes. It is shown that the advantage of the proposed scheme over conventional LoRaWAN communication is up to 100% when short update time and large payload are required. Similar results are obtained regarding the energy efficiency improvement, that is close to 100% for relatively short transmission intervals and long message duration; however, due to the additional overhead for listening the time dissemination messages, efficiency gain can be negative for ve

The monitoring and the management of smart grid require an advanced communication infrastructure. The time synchronization is among the most important services such an infrastructure should offer. Several solutions are available to disseminate the time information in a distributed system; for instance, most of the times a global positioning system (GPS) receiver is used to recover accurate time information. However, GPS receivers need a clear view of the sky. Other solutions, like the use of a network-based synchronization mechanism, require a dedicated communication infrastructure, which is not always feasible for economical reason. Thus, the use of the power grid itself to disseminate a time signal is extremely interesting. The aim of this article is to investigate the possibility to distribute a time signal over a medium voltage (MV) grid using a chirp-based modulation. The timing data are coded using IRIG-B time code. Such an approach does not require the installation of a dedicated infrastructure, and it is noninvasive, because the signal is transmitted on a different band with the respect to power line communication (PLC). The effectiveness of the approach has been experimentally evaluated on a test MV line available in a laboratory. Although the tested chirp-based symbol has a limited frequency bandwidth (80 kHz), the jitter in the identification of the start of frame is on the order of 7.5 μ s, fulfilling the requirements of the most smart grid applications. © 1963-2012 IEEE.

Capacitive sensors are popular, especially due to the possibility to be integrated together with the readout circuit. In particular, differential implementations are intrinsically insensitive to common-mode noise. Unfortunately, stray capacitances can significantly alter the sensor output value, worsening the performance. This article proposes a novel solution based on an autotuning feedback loop to compensate for parasitic effects, thus preserving measurement performance. In particular, a voltage-controlled negative impedance converter is driven by a feedback loop, in order to control the current flowing in the sensor. The proposed solution can work with the both linear and hyperbolic type of sensors and with any voltage-mode sensor interfaces. An experimental setup, comprising the proposed compensating circuit, a De-Sauty bridge-based sensor front end and an emulated sensor, has been arranged to evaluate obtainable performance. Results show that the linearity error is decreased from more than 10%, without compensation, to less than 1%, when the proposed system is applied. © 1963-2012 IEEE.

The use of industrial communication protocols based on Real-Time Ethernet (RTE) standards is completely replacing traditional industrial fieldbuses. As usual, when a technology becomes mature, the need of efficient diagnostic and maintenance tools quickly raises. Very often, following the paradigm of Industry 4.0, the most effective diagnostic systems are today based on distributed, cloud-centric, architectures and artificial intelligence. However, the distributed analysis of RTE systems is challenging, considering the plurality of protocols and the stringent cost constrains which are common in industry. In this paper, a new architecture for the distributed analysis of RTE networks is proposed, leveraging on distributed probes that send traffic samples to Matlab cloud for remote analysis. The paper also proposes a software conversion tool to adapt general PCAP files captured by popular sniffers (e.g. Wireshark) into MAT file for easier Matlab elaboration. Last, a test bench for characterization (in terms of transfer delays) of the first part of the chain for RTE traffic sampling is described. The results show that in less than 10 seconds it is possible to transfer chunks of RTE traffic data (captured on industrial networks with hundreds of real-time devices) directly to the cloud and to have them converted in Matlab format. © 2020 IEEE.

This work deals with the management of sporadic and rare events linked with emergency situations in wireless Internet-of-Things (IoT) scenarios. The goal is to increase the performance of the emergency communication, when low-power wide area networks (LPWANs) are used as IoT backbone. In the proposed approach, a device usually operates as a normal node but, in case of emergency, can use the novel LoRa-REP access method. In this work, the LoRa-REP, based on message replication, is discussed focusing on its capability of reducing average transaction time and increasing success probability. Two operational paradigms have been considered and tested: public LoRaWAN infrastructure with cloud-based backend, and private LoRaWAN networks with local backend (edge/fog computing). Typical examples of public networks are smart cities, whereas local networks are often used in industry or building automation. Additionally, two real use cases (for public and local scenarios) are provided to show the effectiveness of the proposed approach. The experimental results (with a prototype device implementing LoRa-REP and named eNode) show that the success probability of the emergency communication can be increased up to 99.5%, and the average transaction time can be reduced up to 15% with respect to LoRaWAN without retries or up to 50% with respect to LoRaWAN with retries. © 2014 IEEE.

It is common for elderly to experience a decrease in health conditions, limiting independence. Very often, hospitalization is not required and at home assistance is a more effective solution. Ambient assisted living technologies can help in mitigating the need for continuous supervision, enabling the elderly to easily look for help in case of emergency. In this work, the well-known and widespread LoRaWAN communication infrastructure is evaluated for possible complementing indoor and outdoor positioning solutions, in order to alert a remotely-connected caregiver about accidents (e.g., falls). The choice of LoRaWAN is dictated by the capability to implement both private and public infrastructures. Satellite-based systems are addressed for outdoor localization, whereas the demanding task of indoor localization is solved by means of Ultra Wide Band technology. Results demonstrated sub-meter error in a typical indoor scenario, with average communication latency on the order of 700 ms. © 2020 IEEE.

The requirements of distributed systems implemented using IoT paradigms include the sharing of a common time reference. When the applications are intended for industrial scenarios, the desired time synchronization uncertainty decreases, due to the real-time needs of this kind of systems. Currently, the most diffused way to obtain a time reference for an Internet connected device is to use NTP (Network Time Protocol) for querying time servers. This paper is focused on industrial IoT applications and it is aimed to evaluate the impact that NTP synchronization performance and NTP throughput may have on the real-time host network. Analytical formulas for estimating the NTP impact are introduced. The work is complemented by the presentation of a use case that shows the use of NTP for the synchronization of a large industrial plant at field level. The results highlight the threat to the real-time behavior of the automation system caused by the uncontrolled peaks of traffic due to NTP. Last, some design considerations for mitigation of the impact are discussed. © 2020 IEEE.

An early Alzheimer Disease (AD) diagnosis is fundamental for maximizing the effectiveness of treatment administration. Unfortunately, distinguish AD from other neurodegenerative dementias, such as Frontotemporal Dementia (FTD) is not trivial. Transcranial Magnetic Stimulation (TMS) emerged as an effective non-invasive, easy to apply and not time-consuming solution. TMS-based techniques generally require expensive ad hoc clinical equipment that suffer from poor flexibility and user friendliness in defining the specific diagnostic protocol. In this work, a low-cost BeagleBone Black single board computer (BBB-SBC) has been used to implement all the functionalities required to manage a TMS-based instrument. Timeliness of signal generation is guaranteed by dedicated programmable real-time units hosted by the BBB-SBC System on Chip. Web-based interface, complemented by IoT-like features, provide a high degree of versatility and permit the execution of many different diagnostic protocols. In particular, the experimental validation confirms timing error in the sub-microsecond range, more than enough for the considered application. © 2020 IEEE.

Automotive world is changing with the introduction of Intelligent Vehicles. Today, an increasing number of vehicles may send data to the Internet, helping car manufacturer to implement the Industry 4.0 paradigm. The collected data during the lifetime of the vehicles can be used to improve both product and production facilities. Moreover, the availability of additional data coming from onboard sensors could be used to obtain information about the environment surrounding the vehicle. The Smart City scenario includes an extraordinary number of new sensors (in urban area) and vehicles can be thought as additional mobile sensors. This paper describes the prototype of a Vehicle-to-Cloud interface with OBD-II (On Board Diagnostic) communication, 3G/4G connectivity, and LoRaWAN [used as backup channel]. LoRaWAN infrastructures are largely diffused in Smart Cities and they can provide a suitable alternative to cover some areas when 3G/4G fails. Last, considering the Smart City scenarios, this paper discusses the application constrains and design directions to achieve a correct integration between LoRaWAN infrastructure and the Internet of Intelligent Vehicles. © 2020 IEEE.

In the Industry 4.0 the communication infrastructure is derived from the Internet of Things (IoT), and it is called Industrial IoT or IIoT. Smart objects deployed on the field collect a large amount of data which is stored and processed in the Cloud to create innovative services. However, differently from most of the consumer applications, the industrial scenario is generally constrained by time-related requirements and its needs for real-time behavior (i.e., bounded and possibly short delays). Unfortunately, timeliness is generally ignored by traditional service provider, and the Cloud is treated as a black box. For instance, Cloud databases (generally seen as “Database as a service”—DBaaS) have unknown or hard-to-compare impact on applications. The novelty of this work is to provide an experimental measurement methodology based on an abstract view of IIoT applications, in order to define some easy-to-evaluate metrics focused on DBaaS latency (no matter the actual implementation details are). In particular, the focus is on the impact of DBaaS on the overall communication delays in a typical IIoT scalable context (i.e., from the field to the Cloud and the way back). In order to show the effectiveness of the proposed approach, a real use case is discussed (it is a predictive maintenance application with a Siemens S7 industrial controller transmitting system health status information to a Cloudant DB inside the IBM Bluemix platform). Experiments carried on in this use case provide useful insights about the DBaaS performance: evaluation of delays, effects of involved number of devices (scalability and complexity), constraints of the architecture, and clear information for comparing with other implementations and for optimizing configuration. In other words, the proposed evaluation strategy helps in finding out the peculiarities of Cloud Database service implementations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Capacitive sensors are low-cost and robust devices that can be easily scaled to very small sizes, thus making them suitable for implementation as a micro electro-mechanical system (MEMS). Differential arrangements of the sensors are also available, providing improved rejection of common mode interference. Due to their nature, an AC (sinusoidal) excitation signal is usually adopted. Various types of front-end circuits have been proposed in the past, exploiting different techniques such as conversion of capacitance to current or frequency or analog-to-digital conversion and adopting different approaches, such as full analog or full digital architectures. This paper proposes a digital and microcontroller-based system for AC-excited differential sensors aiming at minimizing cost and power needs, in sight of future large volume applications as for Internet of Things (IoT) paradigm. A proof of concept implementation has been realized and experimentally validated, obtaining a relative error in the measurand estimation on the order of 1%, when the parasitic effects can be neglected. © 2020 IEEE.

Home care is an increasing research area; an example is the interest in daily activity and mobility tracking, known to be a strong indicator for people’s health. In particular, the digital mobility assessment of elderly can anticipate and prevent hard clinical events such as falls, that could result in hospitalizations and deaths. In this work, the use of LoRaWAN is verified in a real-world scenario as an effective communication infrastructure for transmitting activity level information to a supervisor structure like a clinic or a hospital. An experimental setup has been purposely implemented to evaluate the feasibility; in particular, the activity level inferred analyzing accelerometers data can be notified with an average delay in the order of 500 ms. © 2020, Springer Nature Switzerland AG.

The LoRaWAN technology, an example of low power wide area network, is considered a possible IoT-derived solution for realizing private cellular (single-hop) communications in the industrial domain. However, despite LoRaWAN promises long range and dense environments with many obstacles (as the industrial ones), it may suffer from coverage issue. Additionally, the inverse relationship between data rates and range may be unacceptable for many industrial applications. In this article, an innovative LoRaWAN range extender (based on an enhanced LoRaWAN node) is described, and its integration in the infrastructure of industrial Internet of Things (IIoT)-enabled industrial wireless networks is presented. A frame relay strategy is suggested, thus avoiding to tradeoff the highest data rates against an increased sensitivity. The feasibility of the solution is formally verified and the features of the realized proof-of-concept prototype, based on commercially available hardware, are discussed. The experimental results, obtained with a purposely designed test bench, show the effectiveness of the proposed approach. In particular, the range extender is transparent for legacy LoRaWAN networks as confirmed by correct relaying of uplink and downlink for different types of LoRaWAN message. © 2005-2012 IEEE.

The new industrial revolution, known as industry 4.0, aims to create value throughout the product life cycle into all industries sectors. In the automotive industry perspective, data can be obtained throughout the life cycle of vehicles if they are appropriately instrumented with an On-Board Diagnostic scanner (OBD-II). Communications interfaces (3G/4G/LoraWan/Wi-Fi) assume essentials rules in order to relay all collected data to services in the cloud. Challenges emerge when using the Low Power, Wide-Area Network (LPWAN) protocols, as the case of LoRaWAN. This article aims to evaluate the feasibility of embedding a data compression algorithm driven by a light-weight evolving real-time approach in order to reduce the amount of data to be transmitted periodically. The proposal was embedded in a low-cost, low-power system on a chip microcontroller based on Edge OBD-II Freematics ONE+™. Results have shown the feasibility of the proposal and indicated compression rates of up to 98% without impact the primary operation of the edge device. © 2020 IEEE.

The application of the most recent advances of the Internet-of-Things (IoT) technology to the automation of buildings is emerging as a promising solution to achieve greater efficiencies in energy consumption, and to allow the realization of sustainable models. The application of IoT has been demonstrated as effective in many fields, such as confirmed, for instance, by the Industry 4.0 concepts, which are revolutionizing modern production chains. By following this approach, the use of distributed control architectures and of IoT technologies (both wired and wireless) would result in effective solutions for the management of smart environments composed of groups of buildings, such as campuses. In this case, heterogeneous IoT solutions are typically adopted to satisfy the requirements of the very diverse possible scenarios (e.g., indoor versus outdoor coverage, mobile versus fixed nodes, just to mention a few), making their large-scale integration cumbersome. To cope with this issue, this paper presents an IoT architecture able to transparently manage different communication protocols in smart environments, and investigates its possible application for the monitoring and control of distributed energy resources in a smart campus. In particular, a use-case focused on the integration of the Long Range Wide Area Network (LoRaWAN) technology is considered to cope with heterogeneous indoor and outdoor communication scenarios. The feasibility analysis of the proposed solution is carried out by computing the scalability limits of the approach, based on the proposed smart campus data model. The results of the study showed that the proposed solution would be able to manage more than 10,000 nodes. An experimental validation of the LoRaWAN technology confirms its suitability in terms of coverage and latency, with a minimum LoRaWAN cell coverage range of 250 m, and a communication latency of about 400 ms. Finally, the advantages of the proposed solution in the supervision and manag

The adoption of the distributed generation paradigm is introducing several changes in the design and operation of modern distribution networks. Modern grid codes are becoming more and more complex, and the adoption of smart protection systems is becoming mandatory. However, the adoption of newer and smarter units is only half of the story. Proper communication networks must be provided as well, and the overall costs may become critical. In this work, the adoption of the Long-Range Wide Area Network (LoRaWAN) technology is suggested as a viable approach to implement the coordination of Interface Protection Systems. A proper communication architecture based on the LoRaWAN Class B technology was proposed and evaluated in order to assess its feasibility for the considered application. A scalability analysis was carried out, by computing the number of devices that can be handled by a single LoRaWAN Gateway (GW) and the maximum expected time of response between a triggering event and the arrival of the related coordination command. The results of the study showed that up to 312 devices can be managed by a single GW, by assuring a maximum response time of 22.95 s. A faster maximum response time of 6.2 s is also possible by reducing the number of managed devices to 12. © 2020 by the authors.

One of the most widespread applications of IoT technologies is smart metering. Despite remote metering in smart grids is not a novelty, the advent of Low Power Wide Area Network (LPWAN) wireless technologies allowed to extend the concept to gas and water distribution. However, these battery-supplied meters must ensure an operating lifetime longer than 10 years without any maintenance, thus leading to battery oversizing. This work focuses on LoRaWAN and proposes an innovative adaptive strategy for equalizing the message time duration in order to maximize the battery exploitation. A simulator has been purposely designed to evaluate the performance in a real-world scenario, considering a node density of hundreds of nodes per square km. The simulation results demonstrate that a better exploitation of the battery is possible, ensuring an increase by 10 times of the amount of the amount of useful user data bytes transferred by meters. © 2020 IEEE.

Recently, designers of the home automation framework are looking to the Internet of Things (IoT) model to make it easier to deploy devices capable of gathering data from various plants. This situation is pushing a further evolution: from the conventional building automation, where the logic is determined by the installer or by the customer, to a cognitive system, capable of learning from the customers' preferences what the best plant configuration would be. The aim of this research work is to identify issues related to the implementation of cognitive solutions during the renovation process of buildings. The paper proposes a cognitive framework to help the operation and management phases of buildings, by means of the digitalization of the supply chain of the construction industry, from the single building aspect to the entire construction cycle. The paper presents the design of smart building elements with integrated capability to generate a massive amount of data for monitoring the energy and maintenance status of renovated buildings. The IoT paradigm has been used to link the physical word of building elements with the cognitive layer. The proposed approach has been applied and validated into a real test case. © 2020 IEEE.