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The digital world offers ample availability of data, both historic and real-time. While this capability has the potential for better decision making, the contrary can be the case for a human actuator. Information overflow causes mental overload rather than empowerment of choice. In the context of traditional supermarket shopping, for example, customers are exposed to unstructured and complex product information including ingredients, nutrition facts, product labels, and more. Processing all this information in the context of multiple sustainability aspects requires expert knowledge. On the other hand, the rise of digitalization and the Internet of Things can be used to assist and empower customers during this shopping process. However, an integrated solution is required to provide a high grade of usability and crucial complexity reduction for customers. Therefore, we outline an IoT decision support system that assists customers on the sales floor and enables better decision making according to personal preferences and sustainable consumption. It integrates an indoor localization system, a product information database, and a ranking system considering the individual shopping preferences, where the latter is specified by the customer within an interactive smartphone application. The discussed IoT decision support system was deployed and tested in two retail stores. Its interaction with non-expert test participants was observed over months, and the results are summarized in this contribution.

A spectacular measurement campaign was carried out on a real-world motorway stretch of Hungary with the participation of international industrial and academic partners. The measurement resulted in vehicle based and infrastructure based sensor data that will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles—equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization—carried out special test scenarios while collecting detailed data using different sensors. All of the test runs were recorded by both vehicles and infrastructure. The paper also showcases application examples to demonstrate the viability of the collected data having access to the ground truth labeling. This data set may support a large variety of solutions, for the test and validation of different kinds of approaches and techniques. As a complementary task, the available 5G network was monitored and tested under different radio conditions to investigate the latency results for different measurement scenarios. A part of the measured data has been shared openly, such that interested automotive and academic parties may use it for their own purposes.

Wireless embedded devices are key elements of Internet-of-Things (IoT) and industrial IoT (IIoT) applications. The complexity of these devices as well as the number of connected devices to networks increase steadily. The high intricacy of the overall system makes it error-prone and vulnerable to attacks and leads to the need to test individual parts or even the whole system. Therefore, this paper presents the concept of a flexible and distributed testbed to evaluate correct behavior in various operation or attack scenarios. It is based on the Robot Operating System (ROS) as communication framework to ensure modularity and expandability. The testbed integrates RF-jamming and measurement devices to evaluate remote attack scenarios and interference issues. An energy harvesting emulation cell is used to evaluate different real-world energy harvesting scenarios. A climatic test chamber allows to investigate the influence of temperature and humidity conditions on the system-under-test. As a testbed application scenario, the automated evaluation of an energy harvesting wireless sensor network designed to instrument automotive engine test benches is presented.

A continually growing number of sensors is required for monitoring industrial processes and for continuous data acquisition from industrial plants and devices. The cabling of sensors represent a considerable effort and potential source of error, which can be avoided by using wireless sensor nodes. These wireless sensor nodes form a wireless sensor network (WSN) to efficiently transmit data to the destination. For the acceptance of WSNs in industry, it is important to build up networks with high trustworthiness. The trustworthiness of the WSN depends not only on a secure wireless communication but also on the ability to detect modifications at the wireless sensor nodes itself. This paper presents the enhancement of the WSN’s trustworthiness using an optical localization system. It can be used for the preparation phase of the WSN and also during operation to track the positions of the wireless sensor nodes and detect spatial modification. The location information of the sensor nodes can also be used to rate their trustworthiness.

Electronic data-sheets that are stored within and provided by a transducer such as ISO/IEC/IEEE 21450 Transducer Electronic Data-sheets are currently intended to ease the utilization of transducers. This is achieved as the data-sheets provide information about sensing and actuation as well as communication capabilities, data formats, calibration information and more. However, so far it can not be ensured that the provided information is trustworthy. Consequently, we propose a concept based on ISO/IEC/IEEE 21450 Transducer Electronic Data-sheets in which signatures and secure elements are used to validate the information in the data-sheets, the manufacturer and calibration labs. Furthermore, this information can be utilised for secure key exchange mechanisms and permission management. This approach ensures that the low-power consumption expected of transducers is still met while providing security and trust.

We present a communication and routing protocol to balance energy consumption among wireless sensor and actuator nodes under the constraint of minimizing end-to-end latency. Minimized and nearly deterministic end-to-end latency allows centralized real time data recording and actuator control. Moreover, defined latency improves security and safety mechanisms to come closer to the trustworthiness of a cable while realizing the advantages of wireless networks. Battery powered or energy harvesting wireless nodes are inevitable to avoid power lines and therefore, we cope with limited energy budgets. In order to balance the communication load among sufficiently supplied nodes, the energy budget is part of the routing path metric. We show that the time domain multiple access scheme is crucial to enable defined latency and improve energy efficiency by avoiding collisions. If the energy distribution among the nodes is known, this novel protocol allows to calculate latency and round-trip time in advance. An asymmetric timing scheme can limit multi-hop latency for either upstream or downstream communication by one superframes (SF) duration. The presented ruleset is able to reconfigure the routing focused on energy constraints of involved nodes.

International Journal of Distributed Systems and Technologies, 8 (4), ISSN:1947-3532, ISSN:1947-3540

Wireless measurement systems will provide significant benefits to industrial applications, for production facilities as well as in mobile or R&D scenarios. However, in order to exploit the improvements by flexibility, scalability and easy reconfigurability brought by wireless sensor networks (WSN), industrial use cases often require a sustainable autonomous energy supply, while providing the reliability which is comparable with today's wired systems. In this work we introduce a sensor node implementation with a temperature measurement circuit design, optimized for low energy consumption, while providing industry-grade accuracy and resolution. A first implementation realizing the concept of a switched signal acquisition circuitry is discussed, demonstrating the impact of the energy harvesting and storage unit. In a second implementation, a coordinated signal conditioning and power management concept is introduced.

Wireless sensor networks (WSNs) are typically used to measure physical quantities of their environment at locations characterized by poor accessibility and lacking of wired infrastructure. To extend the operational time, energy harvesting systems (EHSs) support the power supply by transforming environmental energy into electrical energy. In the best case, a self-sufficient supply of the sensor node is possible. Information about the harvestable energy is necessary to design WSNs and EHSs properly. However, detailed information is often not available and special equipment is necessary to measure it. Therefore, this paper presents a simple method to estimate and track the harvestable power. The results can be used offline for design and simulations of nodes or networks, or online for work-load-distribution or energy aware network routing.

Cyber-physical systems often include small wireless devices to measure physical quantities or control a technical process. These devices need a self-sufficient power supply because no wired infrastructure is available. Their operational time can be enhanced by energy harvesting systems. However, the convertible power is often limited and discontinuous which requires the need of an energy storage unit. If this unit (and thus the whole system) is de-energized, the start-up process may take a significant amount of time because of an inefficient energy harvesting process. Therefore, this paper presents a system which enables a safe and fast start-up from the de-energized state.

Wireless Sensor Networks (WSNs) are at the verge of a broad acceptance in demanding industrial applications. Nodes must fulfill key requirements like reliability and deterministic communication, but also energy autarky in order to allow maintenance-free systems. In this paper a system combining low power, robust communication with appropriate methods for energy harvesting and energy management is suggested. By comparing two alternative variants for powermanagement, constraints of a solar-cell powered node design are derived. The resulting system demonstrates energy sufficiency at standard industrial indoor lighting conditions of 1300 lx for sensor nodes sampling temperature values at 10 Hz and transmitting once per second.

Wireless sensor networks (WSNs) are typically used as interface between the real and digital world. Autonomous sensor nodes of WSNs are placed directly on location to measure physical quantities. Such locations are often characterized by a poor accessibility and no wired infrastructure. These facts cause the need of a dedicated energy supply and some kind of wireless communication. To enable a long operational time, the energy supply should be as energy efficient as possible. So called energy harvesting systems (EHSs) can be used to extend the operational time significantly. The selection of the best configuration of an energy supply is often difficult, because it depends on various influencing factors. This paper presents a methodology to optimize the energy supply using a simulation environment and real world measurements to get realistic results.

Wireless sensor networks are often deployed in harsh environments where they are exposed to extreme conditions. The influences and faults resulting from these conditions are often overlooked. As there are many possibilities for the occurrence of faults, dependability considerations are of high importance. In this work we present an approach for choosing the most adequate parameter set out of a number of qualified parameter sets for an event detection algorithm (EDA). Instead of only considering the performance of the EDA for data that does not contain errors, we analyze the EDA's reaction to erroneous data by injecting different kinds of faults. In a case study, we show how a seemingly optimal parameter set becomes apparent to be having a weak point. We also show how an application engineer can be provided with feedback about weaknesses of the employed EDA and its parameter set, respectively.

Slope monitoring in inner-alpine regions is important for early warning systems to detect potential landslides. Such slopes are often located at areas without wired infrastructure. Thus, wireless sensor networks (WSNs) can be used as measurement and communication system. Each sensor node is equipped with a GPS receiver and is placed in the monitored slope. After transmitting the raw GPS data to the base station, (near) real-time positioning algorithms determine the movement of each sensor node. To achieve accuracy in centimeter range, these algorithms need a continuous data flow of the received GPS signals. This paper presents the integration of an energy harvesting WSN into a reliable data flow process to enable a continuous slope monitoring.

Teaching wireless sensor networks (WSNs) only theoretically is not sufficient to understand the complex interaction of these networks. WSNs consist of sensor nodes which measure physical quantities of their environment, preprocess the measured data, and transmit it towards a base station in a multi-hop manner. WSNs are typically used in application areas without wired infrastructure and so they must be powered by batteries or energy harvesting systems. Due to the influence of different factors on the behavior, practical exercises can enhance the learning process because the students can perform their experimentation independently. This work presents the use of a remote lab for teaching energy harvesting enhanced WSNs. Students can learn the behavior of WSNs and the influences of energy harvesting. Furthermore, practical aspects of WSNs are shown by using a realistic application scenario. This work is part of the European project Remotelabs Access in Internet-based Performance-centered Learning Environment for Curriculum Support.

Wireless sensor networks (WSNs) consist of wirelessly communicating nodes with an autarkic power supply for each node. Typically, the consumable energy of these nodes is very limited. Energy harvesting systems (EHSs) can be used to extend the lifetime or even enable perpetual operation of the sensor nodes. Applicable energy-aware WSN protocols and applications usually raise the complexity such that rough calculations are not sufficient any more. Simulation-based analysis is needed to cope with the complexity of hardware/software interaction and its implications.This work presents a simulation environment which enables combined simulation and performance evaluation of complete WSNs including the sensor nodes' application software, the energy harvesting enhanced hardware, the wireless network communication, and the environment of the sensor nodes.

This contribution reports on a new European project, Remote-labs Access in Internet-based Performance-Centered Learning Environment for Curriculum Support (RIPLECS), in which an official inter-institutional European master degree program in Information and Communication System (ICS) is created. The program is conducted online across five European institutions and is oriented to labor market needs for qualified graduates, with special focus on realizing real-world experiments in each subject remotely. The network architecture of RIPLECS platform enables world-wide distribution of learning resources by utilizing multiple Web servers at several European universities, within a single network topology. The paper discusses the project development stages, implementation and the expected outcomes.

Wireless sensor networks (WSNs) are power critical systems, because they are used in application areas without wired infrastructure. Each sensor node needs a dedicated power supply. Today's protocols and applications for WSNs are often power-aware. However, the state-of-charge (SoC) estimation of the energy storage component (e.g. rechargeable battery) influences the decisions of the power-aware software. A measurement error may cause wrong decisions which would reduce the lifetime of the network. This work presents the simulation results of the impact of an SoC measurement error on the network lifetime running a simple and an enhanced power-aware WSN application. A simulation environment written in SystemC-AMS is used, which enables the combined simulation of the sensor node's application software and its hardware. The simulation shows a reduction of the network lifetime of 3.13% caused by an erroneous measurement. However, the enhanced software is able to increase the network lifetime by 1.66%.

Wireless sensor networks (WSNs) suffer from the lack of wired infrastructure. Each node needs its own power supply, e.g. batteries or energy harvesting systems (EHSs). Typically, EHSs can extend the lifetime of a sensor node or even enable perpetual operation. Due to the high variation of harvestable energy of the environment, the design of the EHSs has to be done very carefully. The design process can be enhanced by using simulation of the WSN including energy harvesting. However, a realistic simulation needs accurate data of the harvestable energy of the environment. This paper presents the concept of an on-site characterization instrument for different types of energy harvesting devices. These instruments can be connected like a WSN.

Wireless sensor networks (WSNs) are typically used in application areas without wired infrastructure or mobility. Therefore, each sensor node needs its own energy supply unit. Sustainable WSNs are powered by energy harvesting systems (EHSs). These systems harvest and buffer the energy from the environment into rechargeable batteries or double layer capacitors. Due to the fact that the connectivity of the WSN depends on every single sensor node, it is important to know the state-of-charge (SoC) of the buffer to determine the remaining operating time. Therefore, each node has to measure its SoC, calculate the remaining operating time and populate this information through the network. The measurement is usually done by an integrated analog-to-digital converter (ADC) of the microcontroller. Each ADC has a specified error that has to be taken into account at the calculations of the remaining operating time. This work presents the error analysis of the SoC measurement using different energy storage components.

Energy efficiency is very important for mobile devices and wireless sensor networks (WSNs), because the consumable energy is limited. Therefore, the operating time of such devices depends mainly on the capacity of the energy storage component and on the average power consumption of the device. The power consumption depends on the supply voltage and on the activated components of the hardware. This work presents the evaluation of component-aware dynamic voltage scaling (CADVS). This low power technique combines the power-down of unused components and the minimization of the supply voltage. Typically, each component of the hardware (microcontroller, transceiver, sensors) has its own supply voltage range. Therefore, the minimum allowed supply voltage depends on the activated components. However, the activated components and consequently the minimum allowed supply voltage varies over time. CADVS uses voltage converter to adjusts the supply voltage of the hardware to save as much energy as possible. This work presents the evaluation of six different voltage converters. It has been shown that CADVS can be used to save up to 38.7% of the energy compared to a constant voltage supply using the introduced scenario while achieving the same end-user performance.

Wireless sensor network (WSN) motes are resource constrained devices. This is due to optimizations tailoring them towards application-specific and cost-efficient scenarios and setups. Many to most of these optimizations are built upon power aware aspects and dependability measures due to the fact that battery technology still evolves quite slowly and WSN's inherent redundancy is suitable for fault-tolerant schemes. What we do here is implementing a programming paradigm where several applications may be distributed heterogeneously among different subsets of a WSN's motes. Multiple applications can be run side by side on the same mote. This is far more efficient than deploying hardware for each and every application. The Multi-Application Mid-dlewAre (MAMA) layer allows running different TinyOS applications at the same time easily. Concurrent sensor usage and messaging is handled by MAMA. Results from simulation runs, hardware deployments, power profiling and scope measurements show good scalability, only little timing and memory overhead and power efficient properties.

Large scale deployments of small, wireless, networked, embedded systems demand for cost reduction in development and maintenance. Most often, this translates into the need for reliable methods for energy conservation as it is the case for wireless sensor networks (WSNs). Our work considers energy harvesting system (EHS)-enhanced WSN technology which is the state-of-the-art technology for perpetual systems supplied from ambient environmental energy. Therefore several aspects have been considered in literature so far: EHS design, energy prediction modeling, harvesting aware media access control (MAC) and routing and finally power management. This paper postulates that identifying and optimizing these aspects on their own does not necessarily lead to feasible solutions. We take a cross-layer perspective and provide a networking protocol for implicit or explicit EHS policy negotiation under the constraint of two prototypical communication patterns. The methods presented show how to combine energy aware routing or conservation from network coding with EHS power management policies under the constraint of state-of-the-art MAC. Evaluation of different end-user communication patterns lets the reader interpret the results for an application at hand.

Energy harvesting systems (EHSs) are the key to perpetual operation of electronic devices in application areas with bad infrastructure or mobility. Wireless sensor networks (WSNs) are often used in such areas. Normal WSN nodes are powered by batteries. Therefore, the lifetime is limited and the batteries have to be replaced manually after a certain period of time. This problem can be solved by EHSs. They exploit energy sources of the environment and store the harvested energy in energy buffers. The EHS supplies the electronic device and ensures a continuous operation. WSNs can benefit from these developments, because the lifetime can be enhanced dramatically. However, the EHS have to be adapted to the requirements of the application area and of the supplied device. This enhances the overall efficiency of EHS. To be able to do that, the fundamental mode of operation of an EHS has to be well-understood. We introduce a novel tier model for EHSs. It structures the EHS into tiers with special functions. This enhances the design process of an EHS, because tiers can be adapted to each other and the overall efficiency of can be increased. The tier model is applied to RiverMote, a WSN node for in-river water level monitoring. Each node is supplied by solar cells and the energy is stored in double layer capacitors (DLCs). The hardware of the EHS of RiverMote is divided into the tiers of the model. These tiers are adapted to each other carefully. Although no maximum power point tracker has been implemented, it has been shown that the available power of the solar cell is greater than 80 % of the maximum power point if the energy level of the DLCs is between 42 % and 100 %. This result was only possible by a careful design and an adaption of the tiers.

Wireless sensor network (WSN) nodes have to cope with severe power supply constraints. Energy harvesting system (EHS) technology is used for prolonging network lifetime. Robust operation of such systems heavily relies on accurate models of EHS efficiency and node power dissipation for calculating sustainable operation modes.

Secure wireless communication is essential for most industrial applications. The secure and reliable control of processes as well as the data integrity of measured values are key targets in these applications. The industrial Internet-of-Things (IIoT) tries to connect an increasing number of sensors wirelessly. The wireless sensors form wireless sensor networks (WSNs). However, wireless sensor nodes are exposed to various security threats ranging from physical modification on the device itself to remote attacks via the communication channel. It is important to secure the complete lifetime of the wireless sensor nodes and other system components. This includes the production phase, shipping, preparation phase and operational phase. This paper presents a lifetime security concept for a wireless sensor network applied in automotive test beds. In this application scenario, the wireless sensor nodes are used to capture various temperatures in an automotive unit under test. In order to indicate the current state of trustworthiness of the system, a trustworthiness indicator is implemented which is shown to the user. An evaluation of the impact of encrypted communication on power consumption shows that the increase is negligible, and can be expected to be provided by the wireless sensor node's power supply without reducing the node lifetime.

Strong need for a sophisticated landslide monitoring and alerting system has grown especially in mountainous regions. Traditionally, monitoring is performed using time-domain reflectometry by geodesists. Since a few years the Global Positioning System (GPS) dual-frequency Real-Time Kinematic (RTK) approach is widely used for monitoring landslides. However, it should be noted that the setup and the support of dual-frequency RTK is cost intensive. In order to reduce the costs of a GPS-based landslide monitoring system, one could use single-frequency low-cost receivers for RTK or try to utilize a Precise Point Positioning (PPP) approach. A landslide monitoring system using both single-frequency RTK and PPP is developed by Graz University of Technology and TeleConsult Austria GmbH within the GeoWSN project. This paper describes the general structure of a GPS-based landslide monitoring system and discusses aspects of the used PPP approach.

Wireless sensor network (WSN) motes are resource constrained devices. Especially, bandwidth and energy are scarce resources. Therefore, lots of effort is put into the optimization of low-power networking protocols. While network control overhead is an issue for many to most of such protocols, we present an approach that is virtually overhead-free. We introduce the implementation of an autonomous network coding implementation that can be implemented for existing applications and added over existing routing mechanisms with no need to change the application or networking protocols. We discuss and carefully evaluate the approach for applicability and gain according to the most prominent optimization metrics for WSN networking protocols. Especially, we consider the comparison of autonomous network coding to state-of-the-art collection protocols and multipath routing. The completely autonomously acting network coding plug-in implementation is profiled to conserve up to 29 % of the messages that need to be sent locally without the need for centralized network control.