Similitudes y diferencias entre Redes de Sensores Inalámbricas e Internet de las Cosas: Hacia una postura clarificadora

Wireless Sensor Network (WSN) and Internet of Things (IoT) are two fields of study, which share, being an autonomous network infrastructure, where objects are interconnected to measure physical variables in scenarios such as logistics, industry, intelligent constructions, security, agriculture, among others. This similarity raises an ambiguity in the academic community's use of the terms WSN and IoT doing blurred the line of where belong the contributions that are made in each of these areas of study. Therefore, the purpose of this article is to analyze the relationship, similarity, and differences between WSN and IoT around five topics, namely: conceptual level, its general requirements and architectures, application construction and data processing. Although WSN and IoT have a common origin, their approaches are different in several ways that clarify the ambiguity arouses among the academic community.Las redes de sensores inalámbricas (WSN) e Internet de las Cosas (IoT) son dos áreas de estudio que comparten entre sí ser una infraestructura de red autónoma, en la cual se interconectan objetos para medir variables físicas y dar solución a problemas en una variedad de escenarios de aplicación, como logística, industria, construcciones inteligentes, seguridad, agricultura, entre otros. Esta semejanza suscita una ambigüedad en el uso que la comunidad académica hace de los términos, WSN e IoT, y hace borrosa la línea de dónde pertenecen las contribuciones que se realizan en cada una de estas áreas. En consecuencia, el objetivo de este artículo es analizar la relación, similitud y diferencias entre WSN e IoT en torno a cinco temas: conceptos, requisitos generales, arquitecturas, aplicaciones y tratamiento de datos. A pesar de que WSN e IoT tienen un origen en común, sus enfoques son diferentes en varios aspectos que permiten aclarar la ambigüedad suscita entre la comunidad académica

Similarities and differences between Wireless Sensor Networks and the Internet of Things: Towards a clarifying position

Las redes de sensores inalámbricas (WSN) e Internet de las Cosas (IoT) son dos áreas de estudio que comparten entre sí ser una infraestructura de red autónoma, en la cual se interconectan objetos para medir variables físicas y dar solución a problemas en una variedad de escenarios de aplicación, como logística, industria, construcciones inteligentes, seguridad, agricultura, entre otros. Esta semejanza suscita una ambigüedad en el uso que la comunidad académica hace de los términos, WSN e IoT, y hace borrosa la línea de dónde pertenecen las contribuciones que se realizan en cada una de estas áreas. En consecuencia, el objetivo de este artículo es analizar la relación, similitud y diferencias entre WSN e IoT en torno a cinco temas: conceptos, requisitos generales, arquitecturas, aplicaciones y tratamiento de datos. A pesar de que WSN e IoT tienen un origen en común, sus enfoques son diferentes en varios aspectos que permiten aclarar la ambigüedad suscita entre la comunidad académica.Wireless Sensor Network (WSN) and Internet of Things (IoT) are two fields of study, which share, being an autonomous network infrastructure, where objects are interconnected to measure physical variables in scenarios such as logistics, industry, intelligent constructions, security, agriculture, among others. This similarity raises an ambiguity in the academic community's use of the terms WSN and IoT doing blurred the line of where belong the contributions that are made in each of these areas of study. Therefore, the purpose of this article is to analyze the relationship, similarity, and differences between WSN and IoT around five topics, namely: conceptual level, its general requirements and architectures, application construction and data processing. Although WSN and IoT have a common origin, their approaches are different in several ways that clarify the ambiguity arouses among the academic community

Strain Energy Harvesting Powered Wireless Sensor System Using Adaptive and Energy-Aware Interface for Enhanced Performance

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.This paper presents a wireless sensor system (WSS) powered by a strain energy harvester (SEH) through the introduction of an adaptive and energy-aware interface for enhanced performance under variable vibration conditions. The interface is realized by an adaptive power management module (PMM) for maximum power transfer under different loading conditions and an energy-aware interface (EAI) which manages the energy flow from the storage capacitor to the WSS for dealing with the mismatch between energy demanded and energy harvested. The focus is to realize high harvested power and high efficiency of the system under variable vibration conditions, and an aircraft wing structure is taken as a study scenario. The SEH powered WSS was tested under different peak-to-peak strain loadings from 300 to 600 µε and vibrational frequencies from 2 to 10 Hz to verify the system performance on energy generation and distribution, system efficiency, and capability of powering a custom-developed WSS. Comparative studies of using different circuit configurations with and without the interface were also performed to verify the advantages of the introduced interface. Experimental results showed that under the applied loading of 600 µε at 10 Hz, the SEH generates 0.5 mW of power without the interface while having around 670 % increase to 3.38 mW with the interface, which highlights the value of the interface. The implemented system has an overall efficiency of 70 to 80 %, a long active time of more than 1 s, and duty cycle of up to 11.85 % for vibration measurement under all the tested conditions.This work was supported in part by the Engineering and Physical Sciences Research Council, U.K., through the project En-ComE-Energy Harvesting Powered Wireless Monitoring Systems Based on Integrated Smart Composite Structures and Energy-Aware Architecture under Grant EP/K020331/1. All data are provided in full in the results section of this paper

Lifetime and Energy Hole Evolution Analysis in Data-Gathering Wireless Sensor Networks

Abstract-Network lifetime is a crucial performance metric to evaluate data-gathering wireless sensor networks (WSNs) where battery-powered sensor nodes periodically sense the environment and forward collected samples to a sink node. In this paper, we propose an analytic model to estimate the entire network lifetime from network initialization until it is completely disabled, and determine the boundary of energy hole in a data-gathering WSN. Specifically, we theoretically estimate the traffic load, energy consumption, and lifetime of sensor nodes during the entire network lifetime. Furthermore, we investigate the temporal and spatial evolution of energy hole, and apply our analytical results to WSN routing in order to balance the energy consumption and improve the network lifetime. Extensive simulation results are provided to demonstrate the validity of the proposed analytic model in estimating the network lifetime and energy hole evolution process. Index Terms-wireless sensor network, network lifetime, energy hole, energy efficiency, routing

Ensuring survivability of resource-intensive sensor networks through ultra-low power overlays

none5siNodes in wireless sensor networks (WSNs) typically have limited power supply and networks are often expected to be functional for extended periods. Therefore, the minimization of energy consumption and the maximization of network lifetime are key objectives in WSN. This paper proposes an overlay, energy optimized, sensor network to extend the functional lifetime of an energy-intensive sensor network application. The overlay network consists of additional nodes that exploit recent advances in energy harvesting and wake-up radio technologies, coupled with an application specific, complementary, ultra-low power sensor. The experimental results and simulations demonstrate that this approach can ensure survivability of energy-inefficient sensor networks. Simulating applications using energy-intensive video cameras and air quality sensors, combined with the proposed overlayed ultra-low power sensor network, demonstrates that this approach can increase functional lifetime toward perpetual operation and is suitable for WSN applications in which complementarity exists between the required energy-intensive sensors and low-cost sensors that can be used as triggers.mixedMagno, Michele; Boyle, David; Brunelli, Davide; Popovici, Emanuel; Benini, LucaMagno, Michele; Boyle, David; Brunelli, Davide; Popovici, Emanuel; Benini, Luc

Localized Application for Video Capture for a Multimedia Sensor Node with Name-Based Segment Streaming

abstract: The Internet of Things (IoT) has become a more pervasive part of everyday life. IoT networks such as wireless sensor networks, depend greatly on the limiting unnecessary power consumption. As such, providing low-power, adaptable software can greatly improve network design. For streaming live video content, Wireless Video Sensor Network Platform compatible Dynamic Adaptive Streaming over HTTP (WVSNP-DASH) aims to revolutionize wireless segmented video streaming by providing a low-power, adaptable framework to compete with modern DASH players such as Moving Picture Experts Group (MPEG-DASH) and Apple’s Hypertext Transfer Protocol (HTTP) Live Streaming (HLS). Each segment is independently playable, and does not depend on a manifest file, resulting in greatly improved power performance. My work was to show that WVSNP-DASH is capable of further power savings at the level of the wireless sensor node itself if a native capture program is implemented at the camera sensor node. I created a native capture program in the C language that fulfills the name-based segmentation requirements of WVSNP-DASH. I present this program with intent to measure its power consumption on a hardware test-bed in future. To my knowledge, this is the first program to generate WVSNP-DASH playable video segments. The results show that our program could be utilized by WVSNP-DASH, but there are issues with the efficiency, so provided are an additional outline for further improvements.Dissertation/ThesisMasters Thesis Computer Engineering 201