Decentralized P2P Broker for M2M and IoT Applications

[Abstract] The recent increase in the number of connected IoT devices, as well as the heterogeneity of the environments where they are deployed, has derived into the growth of the complexity of Machine-to-Machine (M2M) communication protocols and technologies. In addition, the hardware used by IoT devices has become more powerful and efficient. Such enhancements have made it possible to implement novel decentralized computing architectures like the ones based on edge computing, which offload part of the central server processing by using multiple distributed low-power nodes. In order to ease the deployment and synchronization of decentralized edge computing nodes, this paper describes an M2M distributed protocol based on Peer-to-Peer (P2P) communications that can be executed on low-power ARM devices. In addition, this paper proposes to make use of brokerless communications by using a distributed publication/subscription protocol. Thanks to the fact that information is stored in a distributed way among the nodes of the swarm and since each node can implement a specific access control system, the proposed system is able to make use of write access mechanisms and encryption for the stored data so that the rest of the nodes cannot access sensitive information. In order to test the feasibility of the proposed approach, a comparison with an Message-Queuing Telemetry Transport (MQTT) based architecture is performed in terms of latency, network consumption and performance

Design, Implementation and Validation of a Bluetooth 5 Real-Time Monitoring System for Large Indoor Environments

Presented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.[Abstract] The progress of LPWAN technologies in recent years has increased their use in various types of environments as well as increased the applications in which they are used. However, due to the duty cycle limitations of license-free based technologies, they have a considerable limitation for applications with frequent data transmission or real-time data. In this regard, technologies working in the 2.4 GHz band are a compelling option to consider but their main problem concerns their limited range. Fortunately, the new Bluetooth 5 standard has a new feature (Long Range mode) that is especially useful in long distance or large indoor environments. This paper describes a practical study on this new technology for indoor environments. The performed experiments evaluate reception range, communications quality, channel occupancy, response times, and power consumption. The obtained results indicate that a three-floor building of more than 4200 m2 may be covered with a stable signal with only two Bluetooth 5 nodes

Design, Implementation, and Practical Evaluation of a Voice Recognition Based IoT Home Automation System for Low-Resource Languages and Resource-Constrained Edge IoT Devices: A System for Galician and Mobile Opportunistic Scenarios

[Abstract]: Systems with voice control are an attractive option for increasing technological integration, not only for people with little knowledge on technology or constrained Internet access, but also for people with certain disabilities. In addition, devices based on Alexa or Google Home provide an interesting alternative for interacting with Internet of Things (IoT) devices, but they usually rely on an Internet connection to a cloud server for their full operation. Furthermore, many voice-recognition systems are only available in a limited number of languages, which tend to be those with the highest number of speakers, thus excluding minority-language speakers. To address the previously mentioned issues, this article presents a solution based on Edge Computing and voice commands that carries out offline voice processing and that is able to interact with IoT-based systems. The proposed system performs local speech inference, providing a communication interface with IoT devices in a Bluetooth mesh, all in a fast way and without the need for an Internet connection. In addition, the proposed solution can be adapted easily for voice recognition of languages with few resources. Such a feature is demonstrated with the Galician language, which is spoken by less than 3 million people worldwide. In particular, different Automatic Speech Recognition (ASR) models based on three of the most popular ASR development frameworks (wav2vec2, DistilHubert, Whisper) were developed to transcribe short speech and to translate it into IoT commands that perform specific home-automation actions. Such models were fine-tuned for Galician with a corpus of approximately 20 hours and were evaluated in static and mobile opportunistic scenarios in terms of accuracy, energy consumption and latency on an embedded platform (that acts as an edge device) and on a cloud server. The obtained results show that inference is performed in less than 2 seconds on a Raspberry Pi 4 for the two smallest models and in less than 500 ms on a high-end Android smartphone when processing all data locally with CPU-only inference (i.e., without hardware acceleration or external processing). The results of the transcriptions are accurate enough to be able to use simple text distance algorithms to detect keywords in the speech and perform commands on IoT devices. In particular, a maximum success rate of 92% was achieved for detecting the indicated commands when using models optimized for being executed on embedded devices. For selected home scenarios, command actions were sent via Bluetooth with average response times of up to 113 ms.This work has been funded by the Xunta de Galicia (by grant ED431C 2020/15), and by grants PID2020-118857RA-100 (ORBALLO) and TED2021-129433A-C22 (HELENE) funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR.Xunta de Galicia; ED431C 2020/1

Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

[Abstract] Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2016-045Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-

Towards an Autonomous Industry 4.0 Warehouse: A UAV and Blockchain-Based System for Inventory and Traceability Applications in Big Data-Driven Supply Chain Management

[Abstract] Industry 4.0 has paved the way for a world where smart factories will automate and upgrade many processes through the use of some of the latest emerging technologies. One of such technologies is Unmanned Aerial Vehicles (UAVs), which have evolved a great deal in the last years in terms of technology (e.g., control units, sensors, UAV frames) and have significantly reduced their cost. UAVs can help industry in automatable and tedious tasks, like the ones performed on a regular basis for determining the inventory and for preserving item traceability. In such tasks, especially when it comes from untrusted third parties, it is essential to determine whether the collected information is valid or true. Likewise, ensuring data trustworthiness is a key issue in order to leverage Big Data analytics to supply chain efficiency and effectiveness. In such a case, blockchain, another Industry 4.0 technology that has become very popular in other fields like finance, has the potential to provide a higher level of transparency, security, trust and efficiency in the supply chain and enable the use of smart contracts. Thus, in this paper, we present the design and evaluation of a UAV-based system aimed at automating inventory tasks and keeping the traceability of industrial items attached to Radio-Frequency IDentification (RFID) tags. To confront current shortcomings, such a system is developed under a versatile, modular and scalable architecture aimed to reinforce cyber security and decentralization while fostering external audits and big data analytics. Therefore, the system uses a blockchain and a distributed ledger to store certain inventory data collected by UAVs, validate them, ensure their trustworthiness and make them available to the interested parties. In order to show the performance of the proposed system, different tests were performed in a real industrial warehouse, concluding that the system is able to obtain the inventory data really fast in comparison to traditional manual tasks, while being also able to estimate the position of the items when hovering over them thanks to their tag’s signal strength. In addition, the performance of the proposed blockchain-based architecture was evaluated in different scenarios.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-

Low gain avalanche detectors for high energy physics experiments

Trabajo presentado a la 10th Spanish Conference on Electron Devices, celebrada en Aranjuez (Madrid, España) del 11 al 13 de febrero de 2015.This paper describes a new concept of Silicon radiation detector with internal multiplication of the charge generated by the incident particle, known as Low Gain Avalanche Detector (LGAD), with a gain in the range of 10-20. The LGAD is addressed to tracking applications for high energy physics with enhanced performances compared to the conventional detectors based on the PiN diode structure. The physical behavior, the critical design challenges and the first experimental data on the fabricated LGAD prototypes is described in the paper.Peer Reviewe

LoRaWAN and Blockchain based Safety and Health Monitoring System for Industry 4.0 Operators

[Abstract] The latest advances in the different Industry 4.0 technologies have enabled the automation and optimization of complex tasks of production processes thanks to their ability to monitor and track the state of physical elements like machinery, environmental sensors/actuators or industrial operators. This paper focuses on the latter and presents the design and evaluation of a system for monitoring industrial workers that provides a near real-time decentralized response system aimed at reacting and tracing events that affect operator personal safety and health. Such a monitoring system is based on the information collected from sensors encapsulated in IoT wearables that are used to measure both personal and environmental data. The communications architecture relies on LoRaWAN, an LPWAN (Low-Power Wide-Area Network) technology that offers good reliability in harsh communications environments and that provides relatively long distance communications with low-energy consumption. Specifically, each wearable sends the collected information (e.g., heart rate, altitude, external temperature, gas concentration, location) from the sensors to the nearest LoRaWAN gateway, which is transmitted to a pool of nodes where information is stored in a distributed manner. Such a decentralized system allows for providing information redundancy and guarantees its availability as long as there is an operative node. In addition, the proposed system is able to store and to process the collected data through smart contracts in a blockchain, which eliminate the need for a central backend and ensure the traceability and immutability of such data in order to share them with third parties (e.g., insurance companies or medical services).Xunta de Galicia; IN853B-2018/0

A Bluetooth 5 Opportunistic Edge Computing System for Vehicular Scenarios

[Abstract]: The limitations of many IoT devices in terms of storage, computing power and energy consumption require them to be connected to other devices when performing computationally intensive tasks, as happens with IoT systems based on edge computing architectures. However, the lack of wireless connectivity in the places where IoT nodes are deployed or through which they move is still a problem. One of the solutions to mitigate this problem involves using opportunistic networks, which provide connectivity and processing resources efficiently while reducing the communications traffic with remote clouds. Thus, opportunistic networks are helpful in situations when wireless communication coverage is not available, as occurs in certain rural areas, during natural disasters, in wars or when other factors cause network disruptions, as well as in other IoT scenarios in which the cloud becomes saturated (for example, due to an excessive amount of concurrent communications or when denial-of-service (DoS) attacks occur). This article presents the design and initial validation of a novel opportunistic edge computing (OEC) system based on Bluetooth 5 and the use of low-cost single-board computers (SBCs). After describing the proposed OEC system, experimental results are presented for a real opportunistic vehicular IoT scenario. Specifically, the latency and packet loss are measured thanks to the use of an experimental testbed made of two separate IoT networks (each conformed by an IoT node and an OEC gateway): one located in a remote office and another one inside a moving vehicle, which was driven at different vehicular speeds. The obtained results show average latencies ranging from 716 to 955 ms with packet losses between 7% and 27%. As a result, the developed system is useful for providing opportunistic services to moving IoT nodes with relatively low latency requirements.Xunta de Galicia; ED431C 2020/15Xunta de Galicia; ED431G 2019/01Ministerio de Ciencia e Innovación; PID2020-118857RA-I0

The communicative management of large companies in Spain: structure, resources and main challenges of their managers

This article studies the communicative structures of the main companies in Spain. Based on the fact that these organisations have significant economic and human resources, the structure of their communication areas is analysed, as well as the specific training of their top managers. In addition, the article will outline the main concerns that these organisational structures have with regard to the day-to-day management of business communication (transparency, reputation, identity, etc.). To do this, the object of the study is made up of the main companies in the Spanish continuous market, some of them included in the Ibex 35 in 2018. This population has been selected because it has the greatest impact on the national economy and is susceptible to greater information transparency.El presente artículo reflexiona sobre las estructuras comunicativas de las principales empresas españolas. Partiendo de la base de que estas organizaciones tienen importantes recursos económicos y humanos, se analiza la organización de sus áreas de comunicación, las prácticas que llevan a cabo y la formación específica de sus máximos responsables. Además, se detallan las principales preocupaciones y retos de esos departamentos de comunicación en el presente y el futuro inmediato (transparencia, reputación, identidad, etc.). El objeto de estudio lo constituyen las empresas españolas con mayor volumen de facturación, incluyendo las del Ibex 35 en 2018, por ser las de mayor impacto en la economía nacional, además de susceptibles de una mayor transparencia informativa

Continuous Spikes and Waves during Sleep: Electroclinical Presentation and Suggestions for Management

Continuous spikes and waves during sleep (CSWS) is an epileptic encephalopathy characterized in most patients by (1) difficult to control seizures, (2) interictal epileptiform activity that becomes prominent during sleep leading to an electroencephalogram (EEG) pattern of electrical status epilepticus in sleep (ESES), and (3) neurocognitive regression. In this paper, we will summarize current epidemiological, clinical, and EEG knowledge on CSWS and will provide suggestions for treatment. CSWS typically presents with seizures around 2–4 years of age. Neurocognitive regression occurs around 5-6 years of age, and it is accompanied by subacute worsening of EEG abnormalities and seizures. At approximately 6–9 years of age, there is a gradual resolution of seizures and EEG abnormalities, but the neurocognitive deficits persist in most patients. The cause of CSWS is unknown, but early developmental lesions play a major role in approximately half of the patients, and genetic associations have recently been described. High-dose benzodiazepines and corticosteroids have been successfully used to treat clinical and electroencephalographic features. Corticosteroids are often reserved for refractory disease because of adverse events. Valproate, ethosuximide, levetiracetam, sulthiame, and lamotrigine have been also used with some success. Epilepsy surgery may be considered in a few selected patients