Safe Delivery of Sensed Data in Wireless Sensor Networks for Gas Leak Detection: a Boiler Facility Scenario

AbstractIn this work we share our experience in the deployment of a Wireless Gas Sensor Network (WGSN) in an operational boiler facility. Our setup is based on a state-of-the-art WGSN platform which ensures reliable gas detection and long–term operation of the network. We first describe the deployment of the network and then evaluate its wireless links using Received Signal Strenght Indicator (RSSI) and Link Quality Indicator (LQI) metrics

A Self-powered Module with Localization and Tracking System for Paintball

Abstract. In spite of the popularity of wireless sensor networks (WSN), their application scenarios are still scanty. In this paper we apply the WSN paradigm to the entertainment area, and in particular to the domain of Paintball. This niche scenario poses challenges in terms of player localization and wireless sen-sor node lifetime. The main goal of localization in this context is to locate and track the player in order to facilitate his/her orientation, and to increase the level of safety. Long term operation could be achieved by adopting appropriate hardware components, such as storage elements, harvesting component, and a novel circuit solution. In this work we present a decentralized localization and tracking system for Paintball and describe the current status of the development of a self-powered module to be used between a wireless node and an energy harvesting component.

Image Compression and Plants Classification Using Machine Learning in Controlled-Environment Agriculture: Antarctic Station Use Case

In this article, we share our experience in the scope of controlled-environment agriculture automation in the Antarctic station greenhouse facility called EDEN ISS. For remote plant monitoring, control, and maintenance, we solve the problem of plant classification. Due to the inherent communication limitations between Antarctica and Europe, we first propose the image compression mechanism for the data collection. We show that we can compress the images, on average, 7.2 times for efficient transmission over the weak channel. Moreover, we prove that decompressed images can be further used for computer vision applications. Upon decompressing images, we apply machine learning for the classification task. We achieve 92.6% accuracy on an 18-classes unbalanced dataset. The proposed approach is promising for a number of agriculture related applications, including the plant classification, identification of plant diseases, and deviation of plant phenolog

Internet of Things: IoT Infrastructures: Second international summit, IoT 360°

The two-volume set LNICST 169 and 170 constitutes the thoroughly refereed post-conference proceedings of the Second International Internet of Things Summit, IoT 360° 2015, held in Rome, Italy, in October 2015. The IoT 360° is an event bringing a 360 degree perspective on IoT-related projects in important sectors such as mobility, security, healthcare and urban spaces. The conference also aims to coach involved people on the whole path between research to innovation and the way through to commercialization in the IoT domain. This volume contains 62 revised full papers at the following four conferences: The International Conference on Safety and Security in Internet of Things, SaSeIoT, the International Conference on Smart Objects and Technologies for Social Good, GOODTECHS, the International Conference on Cloud, Networking for IoT systems, CN4IoT, and the International Conference on IoT Technologies for HealthCare, HealthyIo

Power Management and Power Consumption Optimization Techniques in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a distributed collection of resource constrained tiny nodes capable of operating with minimal user attendance. Due to their flexibility and low cost, WSNs have recently become widely applied in traffic regulation, fire alarm in buildings, wild fire monitoring, agriculture, health monitoring, building energy management, and ecological monitoring. However, deployment of the WSNs in difficult-to-access areas makes it difficult to replace the batteries - the main power supply of a sensor node. It means that the power limitation of the sensor nodes appreciably constraints their functionality and potential applications. The use of harvesting components such as solar cells alone and energy storage elements such as super capacitors and rechargeable batteries is insufficient for the long-term sensor node operation. With this thesis we are going to show that long-term operation could be achieved by adopting a combination of hardware and software techniques along with energy efficient WSN design. To demonstrate the hardware power management, an energy scavenging module was designed, implemented and tested. This module is able to handle both alternating current (AC) based and direct current (DC) based ambient sources. The harvested energy is stored in two energy buffers of different kind, and is delivered to the sensor node in accordance with an efficient energy supply switching algorithm. The software part of the thesis presents an analytical criterion to establish the value of the synchronization period minimizing the average power dissipated by a WSN node. Since the radio chip is usually the most power hungry component on a board, this approach can help one to decrease the amount of power consumption and prolong the lifetime of the entire WSN. The following part of the thesis demonstrates a methodology for power consumption evaluation of WSN. The methodology supports the Platform Based Design (PBD) paradigm, providing power analysis for various sensor platforms by defining separate abstraction layers for application, services, hardware and power supply modules. Finally, we present three applications where we use the designed hardware module and apply various power management strategies. In the first application we apply the WSN paradigm to the entertainment area, and in particular to the domain of Paintball. The second one refers to a wireless sensor platform for monitoring of dangerous gases and early fire detection. The platform operation is based on the pyrolysis product detection which makes it possible to prevent fire before inflammation. The third application is connected with medical research. This work describes the powering of wireless brain-machine interfaces