Competition: Centrally Scheduled Low-Power Wireless Networking for Dependable Data Collection

For low-power wireless networks, it is important to survive interference to be usable for Industrial Internet-of-Things (IIoT) applications. Distributed flooding protocols like Glossy or Chaos have shown that they can meet the expectations of surviving interference and node failures. However, non-distributed, centralized schedulers are favorable for IIoT but are not used yet in these environments. In this paper, we explore the use of centralized schedulers for low-power wireless networks to achieve robustness in data collection applications

Adaptive Algorithms for Batteryless LoRa-Based Sensors

Ambient energy-powered sensors are becoming increasingly crucial for the sustainability of the Internet-of-Things (IoT). In particular, batteryless sensors are a cost-effective solution that require no battery maintenance, last longer and have greater weatherproofing properties due to the lack of a battery access panel. In this work, we study adaptive transmission algorithms to improve the performance of batteryless IoT sensors based on the LoRa protocol. First, we characterize the device power consumption during sensor measurement and/or transmission events. Then, we consider different scenarios and dynamically tune the most critical network parameters, such as inter-packet transmission time, data redundancy and packet size, to optimize the operation of the device. We design appropriate capacity-based storage, considering a renewable energy source (e.g., photovoltaic panel), and we analyze the probability of energy failures by exploiting both theoretical models and real energy traces. The results can be used as feedback to re-design the device to have an appropriate amount energy storage and meet certain reliability constraints. Finally, a cost analysis is also provided for the energy characteristics of our system, taking into account the dimensioning of both the capacitor and solar panel

Energy harvesting towards self-powered iot devices

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role is played by power management integrated circuits (PMICs), which help to enhance the system's life span. Moreover, PMICs from different manufacturers that provide power management to IoT devices have been discussed in this paper. Furthermore, the energy harvesting networks can expose themselves to prominent security issues putting the secrecy of the system to risk. These possible attacks are also discussed in this review article

High-resolution assessment of air quality in urban areas—a business model perspective

The increasing availability of low-cost air quality sensors has led to novel sensing approaches. Distributed networks of low-cost sensors, together with data fusion and analytics, have enabled unprecedented, spatiotemporal resolution when observing the urban atmosphere. Several projects have demonstrated the potential of different approaches for high-resolution measurement networks ranging from static, low-cost sensor networks over vehicular and airborne sensing to crowdsourced measurements as well as ranging from a research-based operation to citizen science. Yet, sustaining the operation of such low-cost air quality sensor networks remains challenging because of the lack of regulatory support and the lack of an organizational framework linking these measurements to the official air quality network. This paper discusses the logical inclusion of lower-cost air quality sensors into the existing air quality network via a dynamic field calibration process, the resulting sustainable business models, and how this expansion can be self-funded

IoTMapper: a metrics aggregation system architecture in support of smart city solutions

Smart cities are, nowadays, an unavoidable and growing reality, supported on software platforms that support city management, through the processing and presentation of a large number of data, obtained from sensors used throughout the cities. Low-power wide area networks (LPWAN) leverage the sensorization process; however, urban landscape, in turn, induces a high probability of change in the propagation conditions of the LPWAN network, thus requiring active monitoring solutions for assessing the city LPWAN network condition. Currently existing solutions usually consider the existence of only one type of LPWAN network to be monitored. In this paper, an architecture for aggregation of metrics from heterogeneous LPWAN networks is presented. The architecture, named IoTMapper, combines purpose build components with existing components from the FIWARE and Apache Kafka ecosystems. Implementation details for the LPWAN networks are abstracted by adapters so that new networks may be easily added. The validation was carried out using real data collected for long-range wide-area network (LoRaWAN) in Lisbon, and a simulated data set extrapolated from the collected data. The results indicate that the presented architecture is a viable solution for metrics aggregation that may be expanded to support multiple networks. However, some of the considered FIWARE components present performance bottlenecks that may hinder the scaling of the architecture while processing new message arrivals.info:eu-repo/semantics/publishedVersio

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Contribution to the integration, performance improvement, and smart management of data and resources in the Internet of Things

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones.[ENG] This doctoral dissertation has been presented in the form of thesis by publication. The IoT has seen a tremendous growth in the last few years. Not only due to its potential to transform societies, but also as an enabling technology for many other technological advances. Unfortunately, the IoT is a relatively recent paradigm that lacks the maturity of other well-established (not so recent) revolutions like the internet itself or Wireless Sensor Networks; upon which the IoT is built. The presented Thesis contributes to this maturation process by researching on the underlying communication mechanisms that enable a truly ubiquitous and effective IoT. As a Thesis by compilation, 5 relevant articles are introduced and discussed. Each of such articles delve into different key aspects that, in their own way, help closing the gap between what the IoT is expected to bring and what the IoT actually brings. As thoroughly commented throughout the main text, the comprehensive approach taken in this Thesis ensures that multiple angles of the same plane --the communication plane-- are analyzed and studied. From the mathematical analysis of how electromagnetic waves propagate through complex environments to the utilization of recent Machine Learning techniques, this Thesis explore a wide range of scientific and researching tools that are shown to improve the final performance of the IoT. In the first three chapters of this document, the reader will be introduced to the current context and state-of-the-art of the IoT while, at the same time, the formal objectives of this Thesis are outlined and set into such a global context. In the next five chapters, the five corresponding articles are presented and commented. For each and every of these articles: a brief abstract, a methodology summary, a highlight on the results and contributions and final conclusions are also added. Lastly, in the two last chapters, the final conclusions and future lines of this Thesis are commented.Los artículos que componen la tesis son los siguientes: 1. R. M. Sandoval, A.-J. J. Garcia-Sanchez, F. Garcia-Sanchez, and J. Garcia-Haro, \Evaluating the More Suitable ISM Frequency Band for IoT-Based Smart Grids: A Quantitative Study of 915 MHz vs. 2400 MHz," Sensors, vol. 17, no. 1, p. 76, Dec. 2016. 2. R. M. Sandoval, A.-J. J. Garcia-Sanchez, J.-M. M. Molina-Garcia-Pardo, F. Garcia-Sanchez, and J. Garcia-Haro, \Radio-Channel Characterization of Smart Grid Substations in the 2.4-GHz ISM Band," IEEE Trans. Wirel. Commun., vol. 16, no. 2, pp. 1294{1307, Feb. 2017. 3. R. M. Sandoval, A. J. Garcia-Sanchez, and J. Garcia-Haro, \Improving RSSI-based path-loss models accuracy for critical infrastructures: A smart grid substation case-study," IEEE Trans. Ind. Informatics, vol. 14, no. 5, pp. 2230{2240, 2018. 4. R. M. Sandoval, A.-J. Garcia-Sanchez, J. Garcia-Haro, and T. M. Chen, \Optimal policy derivation for Transmission Duty-Cycle constrained LPWAN," IEEE Internet Things J., vol. 5, no. 4, pp. 1{1, Aug. 2018. 5. R. M. Sandoval, S. Canovas-Carrasco, A. Garcia-Sanchez, and J. Garcia-Haro, \Smart Usage of Multiple RAT in IoT-oriented 5G Networks: A Reinforcement Learning Approach," in 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K), 2018, pp. 1-8.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma de Doctorado en Tecnologías de la Información y las Comunicaciones por la Universidad Politécnica de Cartagen