TY - JOUR A1 - Rausch, Lea A1 - Friesen, John A1 - Altherr, Lena A1 - Meck, Marvin A1 - Pelz, Peter F. T1 - A holistic concept to design optimal water supply infrastructures for informal settlements using remote sensing data JF - Remote Sensing N2 - Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data. KW - water supply design KW - mathematical optimization KW - slum classification KW - remote sensing Y1 - 2018 SN - 2072-4292 U6 - https://doi.org/10.3390/rs10020216 VL - 10 IS - 2 SP - 1 EP - 23 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mandekar, Swati A1 - Holland, Abigail A1 - Thielen, Moritz A1 - Behbahani, Mehdi A1 - Melnykowycz, Mark T1 - Advancing towards Ubiquitous EEG, Correlation of In-Ear EEG with Forehead EEG JF - Sensors N2 - Wearable EEG has gained popularity in recent years driven by promising uses outside of clinics and research. The ubiquitous application of continuous EEG requires unobtrusive form-factors that are easily acceptable by the end-users. In this progression, wearable EEG systems have been moving from full scalp to forehead and recently to the ear. The aim of this study is to demonstrate that emerging ear-EEG provides similar impedance and signal properties as established forehead EEG. EEG data using eyes-open and closed alpha paradigm were acquired from ten healthy subjects using generic earpieces fitted with three custom-made electrodes and a forehead electrode (at Fpx) after impedance analysis. Inter-subject variability in in-ear electrode impedance ranged from 20 kΩ to 25 kΩ at 10 Hz. Signal quality was comparable with an SNR of 6 for in-ear and 8 for forehead electrodes. Alpha attenuation was significant during the eyes-open condition in all in-ear electrodes, and it followed the structure of power spectral density plots of forehead electrodes, with the Pearson correlation coefficient of 0.92 between in-ear locations ELE (Left Ear Superior) and ERE (Right Ear Superior) and forehead locations, Fp1 and Fp2, respectively. The results indicate that in-ear EEG is an unobtrusive alternative in terms of impedance, signal properties and information content to established forehead EEG. KW - in-ear EEG KW - correlation KW - forehead EEG KW - impedance spectroscopy KW - biopotential electrodes Y1 - 2022 U6 - https://doi.org/10.3390/s22041568 SN - 1424-8220 VL - 22 IS - 4 SP - 1 EP - 19 PB - MDPI CY - Basel ER - TY - JOUR A1 - Engemann, Heiko A1 - Cönen, Patrick A1 - Dawar, Harshal A1 - Du, Shengzhi A1 - Kallweit, Stephan T1 - A robot-assisted large-scale inspection of wind turbine blades in manufacturing using an autonomous mobile manipulator JF - Applied Sciences N2 - Wind energy represents the dominant share of renewable energies. The rotor blades of a wind turbine are typically made from composite material, which withstands high forces during rotation. The huge dimensions of the rotor blades complicate the inspection processes in manufacturing. The automation of inspection processes has a great potential to increase the overall productivity and to create a consistent reliable database for each individual rotor blade. The focus of this paper is set on the process of rotor blade inspection automation by utilizing an autonomous mobile manipulator. The main innovations include a novel path planning strategy for zone-based navigation, which enables an intuitive right-hand or left-hand driving behavior in a shared human–robot workspace. In addition, we introduce a new method for surface orthogonal motion planning in connection with large-scale structures. An overall execution strategy controls the navigation and manipulation processes of the long-running inspection task. The implemented concepts are evaluated in simulation and applied in a real-use case including the tip of a rotor blade form. KW - mobile manipulation KW - large-scale inspection KW - wind turbine production KW - autonomous navigation KW - surface-orthogonal path planning Y1 - 2021 U6 - https://doi.org/10.3390/app11199271 SN - 2076-3417 N1 - Belongs to the Special Issue "Advances in Industrial Robotics and Intelligent Systems" VL - 11 IS - 19 SP - 1 EP - 22 PB - MDPI CY - Basel ER - TY - JOUR A1 - Franko, Josef A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Duelberg, Enno Sebastian A1 - Engemann, Heiko T1 - Design of a Multi-Robot System for Wind Turbine Maintenance JF - Energies N2 - The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future. Y1 - 2020 U6 - https://doi.org/10.3390/en13102552 SN - 1996-1073 VL - 13 IS - 10 SP - Article 2552 PB - MDPI CY - Basel ER - TY - JOUR A1 - Nobis, Moritz A1 - Schmitt, Carlo A1 - Schemm, Ralf A1 - Schnettler, Armin T1 - Pan-European CVAR-constrained stochastic unit commitment in day-ahead and intraday electricity markets JF - Energies N2 - The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from forecasting errors of variable renewable energies. However, risks associated with uncertain forecasting errors have become increasingly relevant within the process of decarbonization. The intraday market serves to compensate for these forecasting errors. Thus, the uncertainty of forecasting errors results in uncertain intraday prices and quantities. Therefore, this paper proposes a two-stage risk-constrained stochastic optimization approach to fundamentally model unit commitment decisions facing an uncertain intraday market. By the nesting of Lagrangian relaxation and an extended Benders decomposition, this model can be applied to large-scale, e.g., pan-European, power systems. The approach is applied to scenarios for 2023—considering a full nuclear phase-out in Germany—and 2035—considering a full coal phase-out in Germany. First, the influence of the risk factors is evaluated. Furthermore, an evaluation of the market prices shows an increase in price levels as well as an increasing day-ahead-intraday spread in 2023 and in 2035. Finally, it is shown that intraday cross-border trading has a significant influence on trading volumes and prices and ensures a more efficient allocation of resources. Y1 - 2020 U6 - https://doi.org/10.3390/en13092339 SN - 1996-1073 N1 - Special Issue Uncertainties and Risk Management in Competitive Energy Markets VL - 13 IS - Art. 2339 SP - 1 EP - 35 PB - MDPI CY - Basel ER - TY - CHAP A1 - Essingholt, Felix A1 - Meyer, Frederic A1 - Kuhn, Peter A1 - Schmidt, Philip A1 - Benkner, Thorsten A1 - Grabmaier, Anton T1 - Non-invasive heart beat measurement using microwave resonators T2 - Proceedings, Vol. 2, Eurosensors 2018 Conference, Graz, Austria, 9–12 September 2018 Y1 - 2018 U6 - https://doi.org/10.3390/proceedings2131002 SN - 2504-3900 SP - 1002 PB - MDPI CY - Basel ER - TY - JOUR A1 - Engemann, Heiko A1 - Du, Shengzhi A1 - Kallweit, Stephan A1 - Cönen, Patrick A1 - Dawar, Harshal T1 - OMNIVIL - an autonomous mobile manipulator for flexible production JF - Sensors Y1 - 2020 SN - 1424-8220 U6 - https://doi.org/10.3390/s20247249 N1 - Special issue: Sensor Networks Applications in Robotics and Mobile Systems VL - 20 IS - 24, art. no. 7249 SP - 1 EP - 30 PB - MDPI CY - Basel ER - TY - JOUR A1 - Morat, Mareike A1 - Faude, Oliver A1 - Hanssen, Henner A1 - Ludyga, Sebastian A1 - Zacher, Jonas A1 - Eibl, Angi A1 - Albracht, Kirsten A1 - Donath, Lars T1 - Agility Training to Integratively Promote Neuromuscular, Cognitive, Cardiovascular and Psychosocial Function in Healthy Older Adults: A Study Protocol of a One-Year Randomized-Controlled Trial JF - International Journal of Environmental Research and Public Health N2 - Exercise training effectively mitigates aging-induced health and fitness impairments. Traditional training recommendations for the elderly focus separately on relevant physiological fitness domains, such as balance, flexibility, strength and endurance. Thus, a more holistic and functional training framework is needed. The proposed agility training concept integratively tackles spatial orientation, stop and go, balance and strength. The presented protocol aims at introducing a two-armed, one-year randomized controlled trial, evaluating the effects of this concept on neuromuscular, cardiovascular, cognitive and psychosocial health outcomes in healthy older adults. Eighty-five participants were enrolled in this ongoing trial. Seventy-nine participants completed baseline testing and were block-randomized to the agility training group or the inactive control group. All participants undergo pre- and post-testing with interim assessment after six months. The intervention group currently receives supervised, group-based agility training twice a week over one year, with progressively demanding perceptual, cognitive and physical exercises. Knee extension strength, reactive balance, dual task gait speed and the Agility Challenge for the Elderly (ACE) serve as primary endpoints and neuromuscular, cognitive, cardiovascular, and psychosocial meassures serve as surrogate secondary outcomes. Our protocol promotes a comprehensive exercise training concept for older adults, that might facilitate stakeholders in health and exercise to stimulate relevant health outcomes without relying on excessively time-consuming physical activity recommendations. KW - agility KW - prevention KW - healthy aging KW - community dwelling KW - psychosocial Y1 - 2020 U6 - https://doi.org/10.3390/ijerph17061853 SN - 1660-4601 VL - 17 IS - 6 SP - 1 EP - 14 PB - MDPI CY - Basel ER - TY - JOUR A1 - Morais, Paulo V. A1 - Suman, Pedro H. A1 - Schöning, Michael Josef A1 - Siqueira Junior, José R. A1 - Orlandi, Marcelo O. T1 - Layer-by-layer film based on Sn₃O₄ nanobelts as sensing units to detect heavy metals using a capacitive field-effect sensor platform JF - Chemosensors N2 - Lead and nickel, as heavy metals, are still used in industrial processes, and are classified as “environmental health hazards” due to their toxicity and polluting potential. The detection of heavy metals can prevent environmental pollution at toxic levels that are critical to human health. In this sense, the electrolyte–insulator–semiconductor (EIS) field-effect sensor is an attractive sensing platform concerning the fabrication of reusable and robust sensors to detect such substances. This study is aimed to fabricate a sensing unit on an EIS device based on Sn₃O₄ nanobelts embedded in a polyelectrolyte matrix of polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) using the layer-by-layer (LbL) technique. The EIS-Sn₃O₄ sensor exhibited enhanced electrochemical performance for detecting Pb²⁺ and Ni²⁺ ions, revealing a higher affinity for Pb²⁺ ions, with sensitivities of ca. 25.8 mV/decade and 2.4 mV/decade, respectively. Such results indicate that Sn₃O₄ nanobelts can contemplate a feasible proof-of-concept capacitive field-effect sensor for heavy metal detection, envisaging other future studies focusing on environmental monitoring. KW - Sn₃O₄ KW - nanobelts KW - field-effect sensor KW - LbL films KW - heavy metals Y1 - 2023 U6 - https://doi.org/10.3390/chemosensors11080436 SN - 2227-9040 N1 - This article belongs to the Special Issue The Application of Electrochemical Sensors or Biosensors Based on Nanomaterials VL - 11 IS - 8 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schulze, Sven A1 - Feyerl, Günter A1 - Pischinger, Stefan T1 - Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions JF - Energies N2 - To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks. KW - Energy management strategies KW - ECMS KW - CO2 emission reduction targets KW - Driving cycle recognition KW - Predictive battery discharge Y1 - 2023 U6 - https://doi.org/10.3390/en16135171 SN - 1996-1073 N1 - The article belongs to the Special Issue "Energy Management Strategies of Electrified Vehicles toward the Real-World Driving". VL - 16 IS - 13 PB - MDPI CY - Basel ER -