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- Fakultät IuI (58) (remove)
This paper describes the development and test of a novel LiDAR based combine harvester steering system using a harvest scenario and sensor point cloud simulation together with an established simulation toolchain for embedded software development. For a realistic sensor behavior simulation, considering the harvesting environment and the sensor mounting position, a phenomenological approach was chosen to build a multilayer LiDAR model at system level in Gazebo and ROS. A software-in-the-loop simulation of the mechatronic steering system was assembled by interfacing the commercial AppBase framework for point cloud processing and feature detection algorithms together with a machine model and control functions implemented in MATLAB/ Simulink. A test of ECUs in a hardware-in-the-loop simulation and as well as HMI elements in a driver-in-the-loop simulation was achieved by using CAN hardware interfaces and a CANoe based restbus simulation.
The Internet of Things (IoT) relies on sensor devices to measure real-world phenomena in order to provide IoT services. The sensor readings are shared with multiple entities, such as IoT services, other IoT devices or other third parties. The collected data may be sensitive and include personal information. To protect the privacy of the users, the data needs to be protected through an encryption algorithm. For sharing cryptographic cipher-texts with a group of users Attribute-Based Encryption (ABE) is well suited, as it does not require to create group keys. However, the creation of ABE cipher-texts is slow when executed on resource constraint devices, such as IoT sensors. In this paper, we present a modification of an ABE scheme, which not only allows to encrypt data efficiently using ABE, but also reduces the size of the cipher-text, that must be transmitted by the sensor. We also show how our modification can be used to realise an instantaneous key revocation mechanism.
Nach dem Auslaufen der 20-jährigen Förderung über eine Einspeisevergütung im Rahmen des Erneuerbare-Energien-Gesetzes (EEG) gibt es für deutsche Biogasanlagen diverse technische Möglichkeiten für einen Weiterbetrieb. Neben der Wirtschaftlichkeit sind die Anlagenbetreibenden ein wesentlicher Entscheidungsfaktor für den Weiterbetrieb der Anlage. Somit ergibt sich die zentrale Fragestellung „Welche Treiber und Hemmnisse für Betreibende von Bestandsbiogasanlagen in Deutschland bestehen in den verschiedenen Nutzungspfaden für Biogas, sowie für kooperative Geschäftsmodelle?“. Die Erkenntnisse können unter anderem dafür genutzt werden, die Situation der Anlagenbetreibenden besser zu verstehen, um notwendige Unterstützung für einen Weiterbetrieb, beispielsweise durch Kommunen, zur Verfügung stellen zu können.
Artificial intelligence (AI) promises transformative impacts on society, industry, and agriculture, while being heavily reliant on diverse, quality data. The resource-intensive "data
problem" has initialized a shift to synthetic data. One downside of synthetic data is known as the "reality gap", a lack of realism. Hybrid data, combining synthetic and real data, addresses this. The paper examines terminological inconsistencies and proposes a unified taxonomy for real, synthetic, augmented, and hybrid data. It aims to enhance AI training datasets in smart agriculture, addressing the challenges in the agricultural data landscape. Utilizing hybrid data in AI models offers improved prediction performance and adaptability.
Knowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fields or dynamic adaptation of the sampling line during field sampling. An innovative key component is the NUTRI-STAT ISFET sensor module. It measures values for the ions "NO3- ”, “H2PO4- " and "K+ " as well as the pH. The ISFET sensor module was specially developed for soil nutrient analysis. The phosphorus measurement was further developed for the project "soil2data". First results from the ISFET sensor module show a measurement signal settling time of significantly less than 100 seconds and a further consistent stable measurement signal. The measurement signal dynamics of approx. 58 mV per factor 10 of concentration change is given for the measured variables pH and K+. For the measured quantities of NO3- and H2PO4- , the measurement signal dynamics are lower.
Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Funktionen
(2018)
Es werden drei Modellierungsansätze zur Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Fahrzeugfunktionen beschrieben. Das Sensorsignal der Distanzmessung wird dabei anhand realer Messwerte oder phänomenologisch und auf der Basis empirisch ermittelter Kennwerte in Abhängigkeit von objekt- und sensorspezifischen Einflussfaktoren abgebildet. Basierend auf den Methoden zur Simulation von Distanzmesssystemen der Open Source Simulationsumgebung Gazebo wurden die Modellierungsansätze als spezifische Sensor- und Umfeldmodelle implementiert. Die Modelle wurden insbesondere für den Einsatz an mobilen landwirtschaftlichen Arbeitsmaschinen und für die Anwendung in der Getreideernte optimiert.
Recent real-time networking developments have enabled ultra reliability, very low latency and high data rates in wired networks. Wireless networking developments have also shown that they can achieve very high data rates with consistency, but they still lack in providing ultra reliability and extremely low latency. Time Sensitive Networking (TSN) developments have brought these capabilities in Industry automation and Automotive industry too. Although TSN is standardized for wired networks for a long time, for wireless networks it will be standardized within the IEEE 802.11be standard for Wi-Fi and 3GPP Release 17 for 5G in the near future. This paper provides an overview of TSN in wired and wireless networks with the aim of comparing different simulators and presenting their offered functionality and shortcomings. These tools can be used to make oneself familiar with TSN algorithms, standards, and for the development and testing of time sensitive networks. Afterwards, the paper discusses open research questions for using TSN over wireless networks.
Management of agricultural processes is often troubled by disconnections and data transfer failures. Limited cellular network coverage may prevent information exchange between mobile process participants.
The research projects KOMOBAR and ISOCom designed, implemented und field-tested a delay tolerant platform for robust communication in rural areas and challenging environments. An adaptable combination of infrastructure-based cellular networks and infrastructure-free multihop ad hoc communication (WLAN) leads to a variety of new communication opportunities. Temporal storage and forwarding of data on mobile farm machinery as well as dynamic platform configurations during process runtime strongly enhance reliability and robustness of data transfers.
We describe an automated approach, to easily track patients regaining their walking ability while recovering from neurological diseases like e.g. stroke. Based on captured gait data and objective measures derived out of it the rehabilitation process can be optimized and thus steered. In order to apply such system in clinical practice two key requirements have to be fulfilled: (i) the system needs to be applicable in terms of ease of use and performance; (ii) the derived measures need to be accurate.