Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice.

/pdf/a-comprehensive-survey-of-enabling-and-emerging-technologies-30jjnsw3kp.pdf

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing - Part I: Fundamentals and Enabling Technologies

Fifth-generation (5G) networks providing much higher bandwidth and faster data rates will allow connecting vast number of stationary and mobile devices, sensors, agents, users, machines, and vehicles, supporting Internet-of-Things (IoT), real-time dynamic networks of mobile things . Positioning and location awareness will become increasingly important, enabling deployment of new services and contributing to significantly improving the overall performance of the 5G system. Many of the currently talked about solutions to positioning in 5G are centralized, mostly requiring direct communication to the access nodes (or anchors, i.e., nodes with known locations), which in turn requires a high density of anchors. But such centralized positioning solutions may become unwieldy as the number of users and devices continues to grow without limit in sight. As an alternative to the centralized solutions, this paper discusses distributed localization in a 5G-enabled IoT environment where many low power devices, users, or agents are to locate themselves without a direct access to anchors. Even though positioning is essentially a nonlinear problem (solving circle equations by trilateration or triangulation), we discuss a cooperative linear distributed iterative solution with only local measurements, local communication, and local computation needed at each agent. Linearity is obtained by reparametrization of the agent location through barycentric coordinate representations based on local neighborhood geometry that may be computed in terms of certain Cayley–Menger determinants involving relative local inter-agent distance measurements. After a brief introduction to the localization problem, and other available distributed solutions primarily based on directly addressing the nonlinear formulation, we present the distributed linear solution for stationary agent networks and study its convergence, its robustness to noise, and extensions to mobile scenarios, in which agents, users, and (possibly) anchors are dynamic.

Distributed Localization: A Linear Theory

Indoor location identification technologies for real-time IoT-based applications: An inclusive survey

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs.

/pdf/a-comprehensive-survey-of-enabling-and-emerging-technologies-3awz1uijcg.pdf

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing - Part II: Emerging Technologies and Open Issues

Localization and navigation are fundamental issues to mobile robotics. An approach for localization and navigation for a mobile robot in indoor environment is proposed in this paper. In this approach, QR codes are used as landmarks to provide global pose references. Label and location information is stored in QR codes which are strategically placed in the operating environment. The mobile robot is equipped with an industrial camera pointing to the ceiling to read QR codes at high speed. The pose of the robot is estimated according to the positional relationship between QR codes and the robot. For the purpose of collision-free navigation, a laser range finder (LRF) is applied to build a map in unknown environment and detect obstacles. Dijkstra algorithm and Dynamic Window Approach (DWA) are applied in path planning based on a 2D grid map. Experimental results show that this approach has good feasibility and effectiveness.

Localization and navigation using QR code for mobile robot in indoor environment

Inertial navigation systems (INS) are composed of inertial sensors, such as accelerometers and gyroscopes. An INS updates its orientation and position automatically; it has an acceptable stability over the short term, however this stability deteriorates over time. Odometry, used to estimate the position of a mobile robot, employs encoders attached to the robot’s wheels. However, errors occur caused by the integrative nature of the rotating speed and the slippage between the wheel and the ground. In this paper, we discuss mobile robot position estimation without using external signals in indoor environments. In order to achieve optimal solutions, a Kalman filter that estimates the orientation and velocity of mobile robots has been designed. The proposed system combines INS and odometry and delivers more accurate position information than standalone odometry.

/pdf/a-dead-reckoning-localization-system-for-mobile-robots-using-3e2c81ogmo.pdf

A dead reckoning localization system for mobile robots using inertial sensors and wheel revolution encoding

Odometry is a method that calculates the position and heading angle of a mobile robot using encoders attached to the wheels of the robot. Errors in the position and heading angle in odometry continuously increase as the operating time and moving distance increase. The solution to overcome these accumulated errors is to periodically compensate with the external absolute position information. An ultrasonic local positioning system (LPS) consists of multiple ultrasonic transmitters located in the environment and an ultrasonic receiver. In this study, ultrasonic transmitters are in a line at one side, and four transmitters are grouped for a coverage area. In order to measure the time of flights (TOFs) for an ultrasonic signal, the receiver predicted the transmitted time from each transmitter using a hyperbolic model. Four transmitters emit ultrasonic signals sequentially, and then the receiver calculates the position using the present measured distance and the pre-measured distance. In order to extend the distance that is measured, the receiver collects the ultrasonic signal and executes cross correlation with a sinusoidal signal. The measured distance data of the previous step causes the position error. This error is compensated for by the predicted distance data using a bilinear interpolation method. An extended Kalman filter is designed to combine odometry, a compass sensor, and an ultrasonic LPS. The proposed system provides reliable and accurate position and heading information, regardless of the operating time and moving distance.

Positioning of a mobile robot based on odometry and a new ultrasonic LPS

This paper describes the protocol of the in-vehicle network. Nowadays, many cars adopt in-vehicle network for lightweight and maintenance. CAN is popular in-vehicle network for control data, and MOST is network for multimedia data. But CAN and MOST does not integrate and work independently. This paper suggests integration of MOST and CAN. The two networks have different characteristics such as data frame structure, transfer speed, network/bus configuration, etc. So, we implement the MOST/CAN converter that integrates protocols of the two networks by transmitting the CAN data using the MOST asynchronous data channel. To verify the performance of the MOST/CAN converter, we adopt the queuing model and the SAE benchmark data.

Implementation of MOST/CAN network protocol

This paper presents real-time algorithm for an ultrasonic Local Positioning System(LPS). An ultrasonic LPS consists of 4 transmitters and n receivers. Each transmitter transmits an sequential ultrasonic signal to avoid interference of ultrasonic signal. This method is a noneffective application for a fast object. Because receiver detects four sequential transmissive ultrasonic signal and calculates a position. This paper proposes the method which 4 transmitters transmit simultaneous ultrasonic signal and each transmitter distinguished by frequencies and codes. And Auto-Correlation Function(ACF) method separates codes from an ultrasonic echo signal which is interference of each transmitter`s code. If the receiver uses only ACF method, it is difficult to implement real time application for increased computation. This paper implements LPS using dual frequencies and ACF method. Using dual frequencies reduces codes length. The reduced codes length save computation in ACF. To prove this algorithm by experiment, high performance DSP(digital signal processor) used. The result shows the performance of the designed system is good enough positioning.

Implementation of the Ultrasonic Local Positioning System using Dual Frequencies and Codes

Three ultrasonic transmitters are in line at one side and transmit ultrasonic signals that contain different 9bit pseudo-random codes at the same time. The receiver measures time difference of flights (TDOFs) of transmitted signals by optimum correlation detection. According to TDOF, the possible position of the receiver is represented by hyperbolic curves. An intersection of the hyperbolic curves is the position of the receiver. The intersection is calculated by bisection method. The proposed system can be installed easily and the cost of installation is low. In the experimental results, the position errors become large when the receiver is at the position far from central transmitter and are correlated about (u, v) position.

Bong-Su Cho

Papers

A dead reckoning localization system for mobile robots using inertial sensors and wheel revolution encoding

Positioning of a mobile robot based on odometry and a new ultrasonic LPS

Implementation of MOST/CAN network protocol

Implementation of the Ultrasonic Local Positioning System using Dual Frequencies and Codes

Position estimation using hyperbolic model for time difference of flight of ultrasonic