Combining wireless and visual tracking for an indoor environment

There has been a lot of research done towards both camera and Wi-Fi tracking respectively, both these techniques have their benefits and drawbacks. By combining these technologies it is possible to eliminate their respective weaknesses, to increase the possibilities of the system as a whole. This is accomplished by fusing the sensor data from Wi-Fi and camera before inserting it in a particle filter. This will result in a more accurate and robust localization system

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

Dense multipath component polarization and wall attenuation at 1.35 GHz in an office environment

This paper presents an analysis of dense multipath components in office meeting rooms. Radio channel sounding measurements at 1.35 GHz were performed with transmitter and receiver in the same room (intra-room) and in adjacent rooms (inter-room). Specular and dense multipath components were estimated with the RiMAX maximum-likelihood algorithm. The dense multipath reverberation characteristics were found to be not significantly different between polarization subchannels for both the intra-room and the inter-room channels, supporting the validity of a scalar dense multipath model. The specular and dense multipath wall attenuation losses were found to be 12.0 and 5.4 dB, respectively

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

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

Sub-GHz LPWAN network coexistence, management and virtualization : an overview and open research challenges

The IoT domain is characterized by many applications that require low-bandwidth communications over a long range, at a low cost and at low power. Low power wide area networks (LPWANs) fulfill these requirements by using sub-GHz radio frequencies (typically 433 or 868 MHz) with typical transmission ranges in the order of 1 up to 50 km. As a result, a single base station can cover large areas and can support high numbers of connected devices (> 1000 per base station). Notorious initiatives in this domain are LoRa, Sigfox and the upcoming IEEE 802.11ah (or "HaLow") standard. Although these new technologies have the potential to significantly impact many IoT deployments, the current market is very fragmented and many challenges exists related to deployment, scalability, management and coexistence aspects, making adoption of these technologies difficult for many companies. To remedy this, this paper proposes a conceptual framework to improve the performance of LPWAN networks through in-network optimization, cross-technology coexistence and cooperation and virtualization of management functions. In addition, the paper gives an overview of state of the art solutions and identifies open challenges for each of these aspects

Flexible Multimodal Sub-Gigahertz Communication for Heterogeneous Internet of Things Applications

To realize low-power and low-cost wireless communication over long distances, several wireless standards using sub-1 GHz frequencies have recently been proposed, each with their own strengths and weaknesses in terms of coverage, energy consumption, and throughput. However, none of them are currently flexible enough to satisfy the requirements of future dynamic and heterogeneous IoT applications. To alleviate this, a novel architecture that uses a multimodal device for flexibly employing a variety of heterogeneous sub-1 GHz wireless networks is proposed. It greatly increases network flexibility, resilience, and performance. A device design is presented together with an abstraction layer that combines the different networks into a single flexible virtual network substrate. The article elaborates on the qualitative advantages of this approach. Measurement-based simulation results show advantages in terms of energy efficiency, with significant reduction in energy use compared to a single-technology solution in a representative IoT track and trace scenario. Finally, the article identifies several open research challenges that need to be resolved to fully realize this vision of flexible multimodal communication for demanding IoT applications