Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis

In modern transportation, pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians. Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users. Therefore, monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance, which in turn ensures public transportation safety. Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions. Advanced technologies can be employed for the collection and analysis of such data, including various intrusive sensing techniques, image processing techniques, and machine learning methods. This review summarizes the state-of-the-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches

Structural health monitoring of asphalt pavements using smart sensor networks: A comprehensive review

Abstract Early, effective and continuous monitoring allows to reduce costs and to extend life of road infrastructure. For this reason, over the years, more and more efforts have been made to implement more advanced and effective monitoring systems at ever more contained costs, going from impractical manual and destructive methods through automated in vehicle equipment to the most recent wireless sensor network (WSN) embedded into the pavement. The purpose of this paper is to provide a comprehensive, up-to-date critical literature review of wireless sensor networks for pavement health monitoring, considering, also, the experience gained for wired sensor as fundamental point of reference. This work presents both the methodology used to collect and analyse the current bibliography and provides a description and comments fundamental characteristics of wireless sensor networks for pavement monitoring for damage detection purposes, among which energy supply, the detection method, the hardware and network architecture and the performance validation procedures. A brief analysis of other possible complementary applications of smart sensor networks, such as traffic and surface condition monitoring, is provided. Finally, a comment is provided on the gaps and possible directions that future research could follow to allow the extensive use of wireless sensor networks for pavement health condition monitoring

Living IoT: A Flying Wireless Platform on Live Insects

Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201

Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network

Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destination node via multi-hop routing techniques. An appropriate, efficient, and stable routing algorithm must be developed for various VANET applications to address the issues of dynamic topology and intermittent connectivity. Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). The proposed algorithm can adapt to significant changes that may occur in the urban vehicular environment. This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. The validity of the proposed algorithm is investigated by its comparison with ARP-QD protocol, which works on the mechanism of optimal route finding in VANETs in urban environments. Simulation results reveal that the proposed ESRA-MD algorithm shows remarkable improvement in terms of delivery ratio, delivery delay, and communication overhead

3D UAV Trajectory and Communication Design for Simultaneous Uplink and Downlink Transmission

In this paper, we investigate the unmanned aerial vehicle (UAV)-Aided simultaneous uplink and downlink transmission networks, where one UAV acting as a disseminator is connected to multiple access points (AP), and the other UAV acting as a base station (BS) collects data from numerous sensor nodes (SNs). The goal of this paper is to maximize the system throughput by jointly optimizing the 3D UAV trajectory, communication scheduling, and UAV-AP/SN transmit power. We first consider a special case where the UAV-BS and UAV-AP trajectories are pre-determined. Although the resulting problem is an integer and non-convex optimization problem, a globally optimal solution is obtained by applying the polyblock outer approximation (POA) method based on the problem's hidden monotonic structure. Subsequently, for the general case considering the 3D UAV trajectory optimization, an efficient iterative algorithm is proposed to alternately optimize the divided sub-problems based on the successive convex approximation (SCA) technique. Numerical results demonstrate that the proposed design is able to achieve significant system throughput gain over the benchmarks. In addition, the SCA-based method can achieve nearly the same performance as the POA-based method with much lower computational complexity

Bridge Structrural Health Monitoring Using a Cyber-Physical System Framework

Highway bridges are critical infrastructure elements supporting commercial and personal traffic. However, bridge deterioration coupled with insufficient funding for bridge maintenance remain a chronic problem faced by the United States. With the emergence of wireless sensor networks (WSN), structural health monitoring (SHM) has gained increasing attention over the last decade as a viable means of assessing bridge structural conditions. While intensive research has been conducted on bridge SHM, few studies have clearly demonstrated the value of SHM to bridge owners, especially using real-world implementation in operational bridges. This thesis first aims to enhance existing bridge SHM implementations by developing a cyber-physical system (CPS) framework that integrates multiple SHM systems with traffic cameras and weigh-in-motion (WIM) stations located along the same corridor. To demonstrate the efficacy of the proposed CPS, a 20-mile segment of the northbound I-275 highway in Michigan is instrumented with four traffic cameras, two bridge SHM systems and a WIM station. Real-time truck detection algorithms are deployed to intelligently trigger the SHM systems for data collection during large truck events. Such a triggering approach can improve data acquisition efficiency by up to 70% (as compared to schedule-based data collection). Leveraging computer vision-based truck re-identification techniques applied to videos from the traffic cameras along the corridor, a two-stage pipeline is proposed to fuse bridge input data (i.e. truck loads as measured by the WIM station) and output data (i.e. bridge responses to a given truck load). From August 2017 to April 2019, over 20,000 truck events have been captured by the CPS. To the author’s best knowledge, the CPS implementation is the first of its kind in the nation and offers large volume of heterogeneous input-output data thereby opening new opportunities for novel data-driven bridge condition assessment methods. Built upon the developed CPS framework, the second half of the thesis focuses on use of the data in real-world bridge asset management applications. Long-term bridge strain response data is used to investigate and model composite action behavior exhibited in slab-on-girder highway bridges. Partial composite action is observed and quantified over negative bending regions of the bridge through the monitoring of slip strain at the girder-deck interface. It is revealed that undesired composite action over negative bending regions might be a cause of deck deterioration. The analysis performed on modeling composite action is a first in studying composite behavior in operational bridges with in-situ SHM measurements. Second, a data-driven analytical method is proposed to derive site-specific parameters such as dynamic load allowance and unit influence lines for bridge load rating using the input-output data. The resulting rating factors more rationally account for the bridge's systematic behavior leading to more accurate rating of a bridge's load-carrying capacity. Third, the proposed CPS framework is shown capable of measuring highway traffic loads. The paired WIM and bridge response data is used for training a learning-based bridge WIM system where truck weight characteristics such as axle weights are derived directly using corresponding bridge response measurements. Such an approach is successfully utilized to extend the functionality of an existing bridge SHM system for truck weighing purposes achieving precision requirements of a Type-II WIM station (e.g. vehicle gross weight error of less than 15%).PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163210/1/rayhou_1.pd

Weighing-in-motion wireless system for sustainable railway transport

Railway transport is well known as one of the safest and most energy-efficient transport modes, thus favoring its strengthening as part of a sustainable transport system. Yet, the track service life and the quality of the ride on a railway are dependent upon different factors, which can be assessed by a diverse set of technology based systems. In this context, this paper presents the EVO4Rail project that seeks to design, develop and implement a wireless monitoring system for weighing-in-motion and detecting faulty wheels in railway vehicles, positively impacting railway operation, maintenance and management, ultimately aiming at a sustainable rail transport.info:eu-repo/semantics/publishedVersio