Back to Results Prototyping an Energy Harvesting Wireless Sensor Network Application Using HarvWSNet

International audienceIn this article, the HarvWSNet simulation framework is used to explore the feasibility of a structural health monitoring application based on a wireless sensor network. The aim is to show the value of a simulation-based approach for the architecture exploration and prototyping of severely energy constrained applications. In the target application, each network node performs a reading of temperature and/or acceleration and transmits the data to a base station every given period. A second objective of this work is to test the relevance of a power management algorithm whose role is to adapt the application quality of service to the instantaneous state of the energy harvesting module. The final goal is to propose a perpetually powered node architecture compatible with the user application requirements

Hypnos: a Hardware and Software Toolkit for Energy-Aware Sensing in Low-Cost IoT Nodes

Through the Internet of Things, autonomous sensing devices can be deployed to regularly capture environmental and other sensor measurements for a variety of usage scenarios. However, for the market segment of stand-alone, self-sustaining small IoT nodes, long term deployment remains problematic due to the energy-constrained nature of these devices, requiring frequent maintenance. This article introduces Hypnos, an open hardware and software toolkit that aims to balance energy intake and usage through adaptive sensing rate for low-cost Internetconnected IoT nodes. We describe the hardware architecture of the IoT node, an open hardware board based on the Arduino Uno form-factor packing the energy measurement circuitry, and the associated open source software library, that interfaces with the sensing node’s microcontroller and provides access to the low-level energy measurements. Hypnos comes equipped with a built-in, configurable, modified sigmoid function to regulate duty cycle frequency based on energy intake and usage, yet developers may also plug in their custom duty/sleep balancing function. An experiment was set up, whereby two identical boards ran for two months: one with the Hypnos software framework and built-in energy balancing function to regulate sensing rate and the other with fixed sensing rate. The experiment showed that Hypnos is able to successfully balance energy usage and sensing frequency within configurable energy ranges. Hereby, it increases reliability by avoiding complete shutdown, while at the same time optimizing performance in terms of average amount of sensor measurements

Energy challenges for ICT

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT

An Integrated Testbed for Cooperative Perception with Heterogeneous Mobile and Static Sensors

Cooperation among devices with different sensing, computing and communication capabilities provides interesting possibilities in a growing number of problems and applications including domotics (domestic robotics), environmental monitoring or intelligent cities, among others. Despite the increasing interest in academic and industrial communities, experimental tools for evaluation and comparison of cooperative algorithms for such heterogeneous technologies are still very scarce. This paper presents a remote testbed with mobile robots and Wireless Sensor Networks (WSN) equipped with a set of low-cost off-the-shelf sensors, commonly used in cooperative perception research and applications, that present high degree of heterogeneity in their technology, sensed magnitudes, features, output bandwidth, interfaces and power consumption, among others. Its open and modular architecture allows tight integration and interoperability between mobile robots and WSN through a bidirectional protocol that enables full interaction. Moreover, the integration of standard tools and interfaces increases usability, allowing an easy extension to new hardware and software components and the reuse of code. Different levels of decentralization are considered, supporting from totally distributed to centralized approaches. Developed for the EU-funded Cooperating Objects Network of Excellence (CONET) and currently available at the School of Engineering of Seville (Spain), the testbed provides full remote control through the Internet. Numerous experiments have been performed, some of which are described in the paper

Deviation prediction and correction on low-cost atmospheric pressure sensors using a machine-learning algorithm

The datasets used in this work are available in the Zenodo repository, with digital identifier (DOI) as 10.5281/zenodo.3560299.Atmospheric pressure sensors are important devices for several applications, including environment monitoring and indoor positioning tracking systems. This paper proposes a method to enhance the quality of data obtained from low-cost atmospheric pressure sensors using a machine learning algorithm to predict the error behaviour. By using the extremely Randomized Trees algorithm, a model was trained with a reference sensor data for temperature and humidity and with all low-cost sensor datasets that were co-located into an artificial climatic chamber that simulated different climatic situations. Fifteen low-cost environmental sensor units, composed by five different models, were considered. They measure - together - temperature, relative humidity and atmospheric pressure. In the evaluation, three categories of output metrics were considered: raw; trained by the independent sensor data; and trained by the low-cost sensor data. The model trained by the reference sensor was able to reduce the Mean Absolute Error (MAE) between atmospheric pressure sensor pairs by up to 67%, while the same ensemble trained with all low-cost data was able to reduce the MAE by up to 98%. These results suggest that low-cost environmental sensors can be a good asset if their data are properly processed.- (undefined

Survey on wireless technology trade-offs for the industrial internet of things

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

Implementation of an Autonomous Small-scale Car with Indoor Positioning using UWB and IMU

Robotics have had a major impact in the current generation as they have a wide range of uses in manufacturing and automation; therefore, researching new technology related to robotics is currently at a high demand. Indoor robotics, such as automatic guided vehicles or humanoids, is a section of robotics that are mobile and need accurate positioning in order to navigate properly. Thus, research into indoor positioning systems (IPS) has become an interesting research topic to be able to provide a standard in indoor positioning. This thesis tests an ultrawideband (UWB) based IPS and fuses the data from an inertial measurement unit (IMU) using an extended Kalman lter (EKF). The testing platform was implemented using Robot Operating System (ROS) and a Beaglebone Black as the microcontroller for the sensors. However, the main processing was done on a separate laptop. As a result, a proposed smoothing technique was able to provide consistent velocity commands to the vehicle platform without a ecting the data output rate of the UWB based IPS. In line-of-sight (LOS) conditions and a travel length of about 13 m, the best results produced an error of only 0:111 m at the nal point, and an error of up to 0:603 m during travel