Lars Wolf

Applications and evaluations in the area of ultra-low power energy harvesting Wireless Sensor Networks (WSNs) verge toward utilizing state-of-the-art hardware with extremely low power consumption. For the evaluation of these networks, real-world deployments are a common approach where special performance logging hardware is often used in conjunction with the sensor nodes. This hardware needs to be kept simple and cost-effective to allow for scalability. At the same time, it needs to be ensured that the measurement hardware does not interfere with the performance of the sensor node, thereby distorting the evaluation results. Herein lies an especially prominent challenge with ultra-low power sensor nodes. We outline some pitfalls that should be considered when designing or selecting this hardware.

The utilization of IoT devices is becoming omnipresent in industrial settings. However, adoption in more rural areas still poses challenges. Especially when processing data on the edge, privacy, data integrity, accountability and data ownership pose challenges since the devices may be easily accessed and manipulated.We present ContractBox, a system that provides accountable and trusted data sharing based on a publisher–subscriber system, as well as trusted computing on the edge. ContractBox uses a Trusted Execution Environment to guarantee the confidentiality and integrity of clients’ data and code. Furthermore, it provides security by using WebAssembly to execute the smart contracts in their own sandboxed environment. This design protects the host as well as co-located smart contracts from misbehaving executions. Lastly, it ensures the immutability and accountability of the published data by storing it in …

The plethora of applications for Wireless Sensor Networks (WSNs) result in a wide range of environmental conditions for these networks. In many cases, the energy supply is the limiting factor for the lifetime of a network, as changing batteries is very hard or completely unfeasible. Energy harvesting is a very promising concept, as it allows to achieve a theoretically infinite network lifetime. Using Thermoelectric Generators (TEGs) to convert the thermal gradient between the upper soil layers and the ambient air promises energy supply in cases where other commonly used energy sources, such as solar cells, cannot be used due to lack of sunlight. We investigate the performance of a TEG harvester in a long-term experiment. Furthermore, we analyze the energy collected in relation to factors such as sunlight and season and show the feasibility of powering a WSN node from this power source.

Messages in Cooperative-Intelligent Transportation Systems (C-ITS) are secured using cryptography to ensure authenticity and authorization. However, this cannot prevent the semantical incorrectness of the message, which can be caused by either faulty sensors or malicious intent. This misbehavior must be detected and mitigated by receiving stations to prevent harm. Further, misbehaving stations need to be sanctioned by informing their manufacturer, owner, or evicting them from the C-ITS to protect other systems proactively. This misbehavior detection management process of detection, reporting, and sanctioning will be part of European and American Intelligent Transportation Systems (ITS). For research in this domain, we propose the Artery 4 Misbehavior Detection (A4MD) framework, building on the Artery V2X simulation framework and Framework for Misbehavior Detection (F2MD) for the European C-ITS …

In this paper, we illustrate the technological innovations we implemented in a test-bed field to automate the bug scouting process. Our work is motivated by the invasive global pest Halyomorpha halys (HH), whose damages have a huge economic impact for fruit orchards. We propose the automation of the time- and labor-intensive process of the HH scouting, traditionally performed by phytosanitary operators. We then describe the selection criteria that led to the hardware architecture designed consisting of a UAV, an RGB vision chip, a new ad hoc trap, and micro-climate stations. We also look for recognition algorithms based on deep learning models that can learn to recognize the HH after a training based on a dataset of images. Our very preliminary results show that the performances of UAV deep learning algorithms trained on artificial datasets are not satisfactory when tested on real images. However, very …

Various traffic scenarios, whether synthetic or realistic, have been published for the traffic simulator SUMO. Many realistic scenarios containing various traffic situations were used in simulation studies on Cooperative-Intelligent Transportation Systems applications, such as Cooperative Awareness and Collective Perception. However, new applications like Maneuver Coordination (MC) are used in different traffic situations, like on-ramp merging and high-speed overtaking, which are not the focus of present realistic scenarios. To facilitate research in the field of MC, we present and showcase the Frankfurter Kreuz SUMO Traffic (FraST) scenario in this paper. This scenario models highway intersections according to actual usage statistics, presenting a challenging environment for MC.

Currently, Cooperative Awareness is being introduced to evermore commercially available vehicles, and Collective Perception is in the final phase of standardization to be ready as next step (Day 2) of vehicular Cooperative-Intelligent Transportation Systems. Afterwards (Day 3), Maneuver Coordination will be a key functionality for Connected Automated Vehicles. It will enable them to exchange planned trajectories and actively cooperate via Maneuver Coordination Messages (MCMs). Our study presented in this paper analyzes the capacity and performance of an ITS-G5 communication channel employed to exchange these messages, varying a set of different parameters. One of Europe’s most frequented highway intersections was modeled for the simulations, including realistic traffic patterns. Generic channel-centric metrics show that substantial channel loads can be caused, both by existing messages and by …

Invasive species have increasingly become a problem in recent years. Climate change and changing environmental conditions allow them to conquer new habitats. E.g. the Brown Mamorated Stink Bug (lat. halyomorpha halys) (BMSB) has been spreading across Europe and causes significant damage to fruit crops in Italy. To be able to quickly respond to such threats, it is important to understand which environmental conditions are beneficial or harmful for such pests. In this paper, we present a sensor network to help determine the relevant environmental factors for detecting and implementing countermeasures against such pests. We highlight the challenges of designing the system and show the lessons we learned during the deployment and operation of eight months.