During recent years, automation and optimized production processes within a variety of different agriculture sectors allowed farmers to achieve higher harvesting rates and therefore to maximize the outcome of their efforts. Besides harvesting, storing the crop is the next challenging step in improving agricultural practices. Monitoring and adjusting the environmental conditions in storage are important tasks to achieve an optimal and efficient storability. This paper focuses on the communication part of such a monitoring system. Modern warehouses are usually organized as box storage, which means that the crop to be stored is filled into boxes and then piled up in large warehouses. Selective ventilation and air conditioning ensure a maximum storage period. This paper examines which radio frequencies are suitable for transmitting sensor data from stored boxes to a sink. The obtained sensor data could be used, for example, to control the air conditioning of the warehouse more precisely. The investigations are carried out on potatoes as an example, for which first a simulation and then a prototypical sensor node is created.

Energy is the most limiting factor for remote outdoor deployments of Wireless Sensor Networks (WSNs). This paper proposes a novel routing algorithm for dual-platform nodes targeting WSN applications as found in smart farming applications. For scenarios in which high power components of nodes and radio links will be switched on at known points in time, our algorithm tries to make use of scheduled uptimes of nodes with the possibilities to turn other nodes on to send the nodes' data to a sink on time. We compare our method with a traditional flooding-based algorithm as well as with a greedy version which tries to transfer the data immediately. We show that our mechanism works energy-efficient while meeting all deadlines and keeping the amount of control traffic at a necessary minimum.

The fault-tolerant character of WSN protocols and applications that do not assume completely reliable systems legitimize undervolting - a highly efficient energy management technique where the supply voltage is set below the minimum specifications. As has been shown in earlier work, by using thereliable IdealVolting undervolting scheme the lifetime of WSN applications can be increased significantly while keeping the node in a safe state even under rough environmental conditions. To show the usability of undervolting in a real world WSN deployment, we performed a long-term study of IdealVolting in a Smart Farming application. All measurements were performed on a generic outdoor testbed for WSNs (PotatoNet) which is also presented within this paper. We collected a long-term dataset of a WSN running for one farming season on a potato fieldto compare the reliability and performance characteristics of IdealVolting against a regular powered WSN.

Being able to determine the location of a node is of great advantage in many IoT and WSN applications. For example, in health care scenarios or for autonomous configuration of IoT setups this information can be useful. One of the key challenges in localization is to estimate the distance between nodes. Most present indoor localization systems require additional hardware for this estimation which is costly in terms of money and energy consumption. To overcome this disadvantage, we developed a system which is able to perform distance measurements without adding any extra hardware and costs. It is based on phase measurements performed by the IEEE 802.15.4 transceiver chip that is normally solely used to realize communication. In the evaluation we investigate the performance of our system in different real world environments that are typical for IoT and WSN setups.

Automated valet parking services provide great potential to increase the attractiveness of electric vehicles by mitigating their two main current deficiencies: reduced driving ranges and prolonged refueling times. The European research project V-Charge aims at providing this service on designated parking lots using close-to-market sensors only. For this purpose the project developed a prototype capable of performing fully automated navigation in mixed traffic on designated parking lots and GPS-denied parking garages with cameras and ultrasonic sensors only. This paper summarizes the work of the project, comprising advances in network communication and parking space scheduling, multi-camera calibration, semantic mapping concepts, visual localization and motion planning. The project pushed visual localization, environment perception and automated parking to centimetre precision. The developed infrastructure-based camera calibration and semi-supervised semantic mapping concepts greatly reduce maintenance efforts. Results are presented from extensive month-long field tests.

In this paper, we present the usage of our two-platform DTN node "Amphisbaena". It is designed for wireless outdoor operation without the need of an external energy supply. A Low Power Platform is running continuously and is able to power up a Linux based SBC on demand. Both parts are using the same communication protocol and appear as a single node to neighbors. In this demonstration we show the system in an example application, which allows to capture an image from a webcam attached to the High Power Platform. The request for the image is sent using a low power link while the answer is transferred using WiFi from the SBC.

In most Wireless Sensor Network deployments, the energy supply is a major challenge. Especially for nodes with high computational power or high bandwidth communication interfaces, the required size of batteries might increase to infeasible levels, even if the option of energy harvesting exists. For many use cases, some nodes are idling most of the time and transmitting only a few bytes from time to time. In this paper, we present a two-platform node consisting of a high-power and a low-power platform. Both platforms are using the same Delay-Tolerant Networking (DTN) architecture and the same protocols. A novel concept offers the opportunity for both platforms to appear as a single node to communication partners. The high-power part is running a full-featured Linux operating system, the low power platform is built around an energy-efficient 32-bit microcontroller and is able to fulfill tasks, which would have required to wake up the high power node in a conventional setup. Our system can increase the energy efficiency in WSN scenarios where the demand of bandwidth and computational performance is strongly fluctuating.

The deployment and especially the long-term operation of outdoor Wireless Sensor Network (WSN) testbeds is still a challenging task. If different monitoring tasks with significantly varying demands have to be performed, the handling of scarce resources like energy becomes difficult and might lead to questions about the reliability of the testbed. In this paper, we present "PotatoMesh", a remotely deployed WSN consisting of different classes of nodes. In addition to more regular sensor nodes like INGA [1], we introduce new 'two-platform' nodes which consist out of a higher and a lower processing & communication performance part. Several, different tasks can be assigned to the nodes. Depending on the needs of the tasks, they may be executed on the more energy-efficient low-power part or lead to the boot up of the high-power platform. Experiences made from this deployment are used to create new energy-efficient routing schemes for self-powered wireless network deployments.

In the past we presented a delay tolerant network that used public buses and trams in the city of Braunschweig to monitor air pollution. Today, as smartphones are becoming computationally more powerful and offer a variety of communication interfaces, it becomes attractive to investigate whether smartphones and vehicular nodes can cooperate with each other, forming a network that can provide better quality of service to applications. In this paper, we evaluate the feasibility of creating an integrated Delay- and Disruption-Tolerant Network (DTN) consisting of smartphones and the public transportation system. Most importantly we propose a Misbehavior Detection System (MDS) to protect the security of the hybrid network. The evaluation results show that our MDS is able to efficiently detect attackers and defend the hybrid network against the interference of malicious nodes.

Future requirements for drastic reduction of CO2production and energy consumption will lead to significant changes in the way we see mobility in the years to come. However, the automotive industry has identified significant barriers to the adoption of electric vehicles, including reduced driving range and greatly increased refueling times. Automated cars have the potential to reduce the environmental impact of driving, and increase the safety of motor vehicle travel. The current state-of-the-art in vehicle automation requires a suite of expensive sensors. While the cost of these sensors is decreasing, integrating them into electric cars will increase the price and represent another barrier to adoption. The V-Charge Project, funded by the European Commission, seeks to address these problems simultaneously by developing an electric automated car, outfitted with close-to-market sensors, which is able to automate valet parking and recharging for integration into a future transportation system. The final goal is the demonstration of a fully operational system including automated navigation and parking. This paper presents an overview of the V-Charge system, from the platform setup to the mapping, perception, and planning sub-systems.