Subharthi Banerjee

A New Railyard Safety Approach for Detection and Tracking of Personnel and Dynamic Objects Using Software-Defined Radar

In a typical railyard environment, a myriad of large and dynamic objects pose significant risks to railyard workers. Unintentional falls, trips and collisions with dynamic rolling stock due to distractions or lack of situational awareness are an unfortunate reality in modern railyards. The challenges of current technologies in detecting and tracking multiple differently-sized mobile objects in situations such as i) one-on-one, ii) many-to-one, iii) one-to-many, iv) blind spot, and v) interfering/non-interfering separation creates the possibility for reduction or loss of situational awareness in this fast-paced environment. The simultaneous tracking of assets with different size, velocity and material composition in different working and environmental conditions can only be accomplished through joint infrastructure-based asset discovery and localization sensors that cause no interference or impediment to the railyard workers, and which are capable of detecting near-misses as well. Our team is investigating the design and performance of such a solution, and is currently focusing on the innovative usage of lightweight low-cost RADAR under different conditions that are expected to be encountered in railyards across North America. We are employing Ancorteks 580-AD Software Defined RADAR (SDRadar) system, which operates at the license-free frequency of 5.8 GHz and with a vari∗Address all correspondence to this author. ety of different configuration options that make it well-suited for generalized object tracking. The challenges, however, stem from the unique interplay between tracking large metallic objects such as railcars, locomotives, and trucks, as well as smaller objects such as railyard workers, in particular their robust discernment from each other. Our design‘s higher-level system can interact with the lower-level SDRadar design to change the parameters in real-time to detect and track large objects over significant distances. The algorithm optimally adjusts waveform, sweep time and sample rate based on one or multiple detected object crosssections and subsequently alters these parameters to be able to discern other objects from them that are in close proximity. We also use an ensemble method to determine the velocity and distance of target objects to accurately track the subject and larger objects at a distance. The methodology has been field-tested with several test cases in a multitude of weather and lighting conditions. We have also tested the proper height, azimuth and elevation angles for positioning our SDRadar to alleviate the risk of blind spots and enhancing the detection and tracking capabilities of our algorithm. The approach has outperformed our previous tests using visual and acoustic sensors for detection and tracking railroad workers in terms of accuracy and operating flexibility. In this paper, we discuss the details of our proposed approach and present our results from the field tests. Proceedings of the 2018 Joint Rail Conference JRC2018 April 18-20, 2018, Pittsburgh, PA, USA

UPWARC: User plane wireless adaptable reliable communication, a new architecture for high speed train passenger internet services

There has been renewed attention given to High Speed Railways (HSR) in the US, in terms of adapting more speed, reliability, increasing passenger capacity and providing passenger centric services. Any future Train-To-Ground (T2G) communication system therefore has to embrace reliable signaling and control-specific needs of HSR, while also catering towards the high performance networking demands of passengers. Segregation of T2G traffic into multi-frequency user/control plane separated traffic based on these respective requirements of train and passenger services may therefore provide a unique opportunity to US railroads to achieve a cost-effective yet future-proof solution fully embracing fifth-generation wireless communication paradigms. Built upon this vision we propose a logical cell and sector-based multi-railcar MIMO solution for railroad micro-/mmWave base stations to support the high performance demand imposed upon user plane traffic in HSR. The logical cells and sectors are developed solely based on railcar outdoor antennas, which can provide an optimal performance throughout the coverage area, regardless of the track-to-base station distance. The proposed UPWARC simulation results have shown great reliability and spectral efficiency compared to the conventional architectures. This is due to attaining optimality and granularity in network design, exploiting precise operation of high speed train and linear movement.

A review of workspace challenges and wearable solutions in railroads and construction

Railroad environments are generally considered to be dangerous workplace environments. The types of risks encountered there are comparable to the construction industry, ranking among the highest in workplace fatalities. However, these two industries also employ millions of people and thus safety has always been a major concern to both industries. These efforts, by industry and academia, are now starting to take an approach to collect safety related data for further analysis to comprehensively improve worker safety. Recent advances in wearable devices have greatly enhanced safety and data analytics by providing workers an advanced layered protection and also acquiring real-time incident data. In this paper we survey the challenges in these work environments to employee safety as well as wearable solutions currently designed to detect risks and alert workers of these situations. We aim to determine the current state of the art technologies in Wireless Body Area Network (WBAN), capable of addressing work environment challenges in railyards. Similarly, wearable solutions in the construction industry are evaluated for their feasibility to protect railyard workers.

Novel concept of D2D mobility modeling utilizing biological cell jamming/unjamming paradigm

The effects of human mobility in Device-to-Device (D2D) communication are not well understood, but with the recent proliferation of D2D, communications have become a critical research emphasis. However, very little is understood on how human mobility and D2D communication are interdependent. The unpredictability of human mobility is one of the root causes in properly visualizing and designing an efficient D2D system framework. The impact of mobility, heterogeneous cell size and distribution, the presence of multiple channel access methods and movement behavior lead to nearly insurmountable challenges in modelling D2D comprehensively and accurately. Thus, to address these challenges our work leverages and extends upon a novel concept from biology and the human mobility model STEPS - that of shape-based cellular jamming and unjamming. Novel and recent studies in the medical domain infer the fundamental reasons for biological cellular jamming as a consequence of distortion in cell shapes. In this paper, a similar analogy of jamming and interaction based distortion in mobility has been used to investigate a novel approach to accurately capture and depict group-based human mobility and its states.

Fusion of VR and teleoperation for innovative near-presence laboratory experience in engineering education

Distance learning is becoming a popular mode of learning among individuals seeking to add new skills to their repertoire or acquire an advanced degree. The availability of online course materials from institutions in academia aid this process, lending standardized and validated information to the audience seeking such knowledge. Although the online system of learning is extremely convenient for acquiring theoretical knowledge, the scope of hands-on experience is limited to the use of simulation software or involves the purchase of expensive laboratory kits. The proliferation of new technology like Virtual Reality (VR), Fifth Generation cellular networks (5G), and industrial robotics can be leveraged to bridge this gap, however. This will enable effective delivery of traditional disciplines like Electrical, Computer, or Mechanical Engineering using the online mode. This paper discusses the enabling technologies for implementing such a system. An ongoing effort to establish a proof-of-concept system in the Electrical and Computer Engineering department of the University of Nebraska-Lincoln is presented.

Decoupled U/C plane architecture for HetNets and high speed mobility: research directions & challenges

The goal of this paper is to explore the evolution of Heterogeneous Networks (HetN ets) and their move towards SG in robust high speed mobile wireless networks. The recent advent of SG provides concepts for low-latency and high capacity network solutions that can be integrated into fast moving architectures. However, the challenges in deploying and utilizing the conventional HetNets have led to new architectures that address the disparate needs of user and control traffic, particularly the concept of decoupling user and control plane operations. The aim of this design goal is to enhance the reliability in narrowband low frequency channels used for high-priority control traffic, while allocating the high-volume user traffic burden into wideband high frequency channels. Inherent in this paradigm shift, however, there exists a wide range of unique design challenges. Thus, in this paper we explore the advantages of User/Control Decoupled Architectures (UCDA) compared to Software Defined Networks (SDN), Cognitive Radio (CR), and the Long Term Evolution (LTE) architecture, as well as their respective disadvantages in high speed mobility scenario.

Towards a modular IoT network model: Low power radio domain use-case in linear-topology wireless sensor network

The Internet of Things (IoT) is a new paradigm that envisions ubiquitous connectivity. It provides new ways in which distributed systems can be imagined with devices communicating with each other and also with humans. The data provided by such a large, heterogeneous network can be leveraged to provide enhanced services to society and solve problems previously deemed impossible. Most devices in IoT are resource constrained hence their performance metrics like throughput, latency and energy requirements are critical design parameters. There needs to be an efficient way in which deployments of IoT can be quickly modelled and their metrics predicted for further tuning and optimization. Currently, most modelling approaches concentrate on homogeneous mesh-like networks. The approaches also tend to model the network as a single phenomenon which is seldom the scenario in an IoT deployment. In this work we utilize a linear chain-like topology of wireless sensors utilizing ContikiMAC as a use-case. We introduce a modular network modelling approach to predict the metrics of the network deployment which is typically seen in pipeline monitoring, water quality monitoring, on-board freight train status monitoring among other scenarios. The model predicts behavior of nodes in a linear chain-like topology utilizing ContikiMAC protocol for multi-hop communication with a sink node.