Urban Living Lab for Local Regeneration. Beyond Participation in Large-scale Social Housing Estates

Living Labs are increasingly promoted as innovative tools for urban regeneration in Europe. In this contribution, we look at their potential in the context of the regeneration of large-scale social housing estates. Starting from the results of the research project SoHoLab (2017–2020) and building on the contributions of this book, we identify Living Labs as practices that are at the margin of key regeneration processes and actors but that nonetheless play an important, enabling role in triggering a more broadly supported approach to regeneration. We use the metaphor of the ‘interstice’ to identify Living Labs’ role of mediating across different social, institutional, disciplinary, departmental, and policy realms. Nevertheless, caution is warranted. Living Labs should not be considered the approach towards the urban regeneration of marginalized areas; their potential lies precisely in their hybrid and constantly transforming character. To steer regeneration practices and policies that are more inclusive, they should be accompanied by a critical and self-reflexive research attitude

Identification of quasi-optimal regions in the design space using surrogate modeling

The use of Surrogate Based Optimization (SBO) is widely spread in engineering design to find optimal performance characteristics of expensive simulations (forward analysis: from input to optimal output). However, often the practitioner knows a priori the desired performance and is interested in finding the associated input parameters (reverse analysis: from desired output to input). A popular method to solve such reverse (inverse) problems is to minimize the error between the simulated performance and the desired goal. However, there might be multiple quasi-optimal solutions to the problem. In this paper, the authors propose a novel method to efficiently solve inverse problems and to sample Quasi-Optimal Regions (QORs) in the input (design) space more densely. The development of this technique, based on the probability of improvement criterion and kriging models, is driven by a real-life problem from bio-mechanics, i.e., determining the elasticity of the (rabbit) tympanic membrane, a membrane that converts acoustic sound wave into vibrations of the middle ear ossicular bones

Electrical characterization of P3HT:PCBM organic solar cells by admittance spectroscopy: defect investigation

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Combining TDoA and AoA with a particle filter in an outdoor LoRaWAN network

Internet of Things (IoT) applications that value long battery lifetime over accurate location-based services benefit from localization via Low Power Wide Area Networks (LPWANs) such as LoRaWAN. Recent work on Angle Of Arrival (AoA) estimation with LoRa enables us to explore new optimizations that decrease the estimation error and increase the reliability of Time Difference Of Arrival (TDoA) methods. In this paper, particle filtering is applied to combine TDoA and AoA measurements that were collected in a dense urban environment. The performance of this particle filter is compared to a TDoA estimator and our previous grid-based combination. The results show that a median estimation error of 199 m can be obtained with a particle filter without AoA, which is an error reduction of 10 % compared to the grid-based method. Moreover, the median error is reduced with 57 % if AoA measurements are used. Hence, more accurate and reliable localization is achieved compared to the performance of other baseline methods

MapFuse: Complete and Realistic 3D Modelling

Validating a 3D indoor radio propagation model that simulates the signal strength of a wireless device can be a challenging task due to an incomplete or a faulty environment model. In this paper, we present a novel method to simulate a complete indoor environment that can be used for evaluating a radio propagation model efficiently. In order to obtain a realistic and robust model of the full environment, the OctoMap framework is applied. The system combines the result of a SLAM algorithm and secondly a simple initial model of the same environment in a probabilistic way. Due to this approach, sensor noise and accumulated registration errors are minimised. Furthermore, in this article, we evaluate the merging approach with two SLAM algorithms, three vision sensors, and four datasets, of which one is publicly available. As a result, we have created a complete volumetric model by merging an initial model of the environment with the result of RGB-D SLAM based on real sensor measurements

LoRaWAN geo-tracking using map matching and compass sensor fusion

In contrast to accurate GPS-based localization, approaches to localize within LoRaWAN networks offer the advantages of being low power and low cost. This targets a very different set of use cases and applications on the market where accuracy is not the main considered metric. The localization is performed by the Time Difference of Arrival (TDoA) method and provides discrete position estimates on a map. An accurate "tracking-on-demand" mode for retrieving lost and stolen assets is important. To enable this mode, we propose deploying an e-compass in the mobile LoRa node, which frequently communicates directional information via the payload of the LoRaWAN uplink messages. Fusing this additional information with raw TDoA estimates in a map matching algorithm enables us to estimate the node location with a much increased accuracy. It is shown that this sensor fusion technique outperforms raw TDoA at the cost of only embedding a low-cost e-compass. For driving, cycling, and walking trajectories, we obtained minimal improvements of 65, 76, and 82% on the median errors which were reduced from 206 to 68 m, 197 to 47 m, and 175 to 31 m, respectively. The energy impact of adding an e-compass is limited: energy consumption increases by only 10% compared to traditional LoRa localization, resulting in a solution that is still 14 times more energy-efficient than a GPS-over-LoRa solution

Effect of ultrasonic homogenization on the Vis/NIR bulk optical properties of milk

status: publishe