Open Transit Data (OTD) availability presents an excellent opportunity for commuter-centric applications. Applications that use OTD to inform users about their commute. Moreover, the current scenario demands applications that make travel in public transit safer and more comfortable. To this cause, we present a contactless e-ticketing solution for public transport buses allowing passengers to purchase tickets in a contactless manner. It is currently in a trial phase since September and has sold over 200k tickets. The system also presents opportunities for third-party vendors to develop similar solutions.

Autonomous Networking is expected to be the mode of functioning by future networks, including 5G wireless networks. This requires intelligent data analytics and cognitive capabilities to be inherently supported as part of the networking functions, in addition to the current capabilities such as automation and correlation. This demonstration presents CygNet MaSoN, a management system that integrates multiple instances of radio access and core network functions of 5G networks supporting advanced aggregation and analytics features. This system continuously collects critical data related to network and system events, performance measurements and key performance indicators (KPIs) in real-time. It then uses the associated machine learning system to provide insights on network behaviour, estimation of service quality/experience and prediction of probable future network problems. Some of the analytics and machine learning use cases related to 5G networks and implemented on the MaSoN system are also described.

This demonstration will present the operation and main features of the 5G Core software system based on 3GPP Release 16. The system is being developed as part of the Indigenous India 5G testbed project, led by IIT Madras. The core software is based on Network Function Virtualization concepts and the Service Based Architecture (SBA). The main features to be demonstrated in the current version will be UE (de)registration, PDU session establishment and release.

We present a co-emulation framework for Connected Autonomous Vehicle for development and validation of technologies for teleoperation of semi-autonomous vehicles. Despite several technical advancements in the autonomous vehicles' domain, Automated Driving System (ADS) deployments were limited to SAE level-3. Remote driving capability offers a promising fallback option. In order to establish a technology stack over existing and new network infrastructure, we need a simulation or emulation framework, to test the system before deploying it on the road. Our framework enables testing with an actual vehicle and a simulated network, and we demonstrate a tele-driving use-case of a retrofitted electric car.

COVID-19 pandemic has impacted millions of people worldwide. To tackle the spread of disease, governments all over the world had to impose sudden lockdowns with strict restrictions and has resulted in stressing most of the enterprises on the financial fronts. As the government is now relaxing the restrictions, businesses are re-opening gradually and employees are returning back to work. There is huge responsibility on the enterprises to stay vigilant when an employee tests positive for COVID-19. To target the issue, we have come up with a contact tracing solution, P-Tracer application which uses users wifi association data from Arista Networks' Cloud-Vision Wifi. This demo paper shortly presents the P-Tracer application working principle a. We claim that the app will be useful in tracing the users association journey and detection of new hot zones and possible new cases.

We present VibranSee, a visible light-based prototype system that jointly achieves communication and sensing of mechanical vibrations by employing optical strobing and high-frequency signal modulation concurrently.

Multi-access Edge Computing (MEC) is an evolving technology and considered as one of the critical enablers for technologies to meet the IMT definition of 5G communications. It integrates the service provider's network with the high-performance computation facility to cater to various applications such as augmented reality, vision applications, etc., at the network edge. Thus, reducing the overall latency and preserving the bandwidth to send the complete data to the centralized data centers for processing instead. Furthermore, MEC opens up tremendous business opportunities for telecommunication companies by offering a service platform for deploying various services specific to consumers and industry at the network edge. In this work, we have demonstrated a full-fledged MEC architecture, including its entities, and integrated with 5G core following ETSI 5G specification with an application deployment use-case. The various MEC and 5G core components are instantiated in the virtual machine as a guest; the complete data path and control path is established between all core components following a service-based architecture. The MEC system developed is a part of the indigenous 5G Test-Bed project and follows the ETSI architecture. The developed system is suitable for executing various applications that require data offloading, extensive storage and computing resources. Thus, our working MEC system establishes a proof of concept and closely resembles a real-world deployment of MEC system in 5G environment.

3GPP 5G New Radios are expected to operate not only on the licensed bands but also on the unlicensed and shared bands. To process such a wideband spectrum, the base stations should be capable of characterizing the wideband spectrum. Moreover, since multi-antenna and beamforming are de-facto approaches in 5G, characterization of spectrum is desired over both time as well as spatial domains. In this demonstration, we develop an intelligent and reconfigurable architecture for non-contiguous wideband spectrum characterization which involves the recovery of wideband band spectrum and determination of occupancy status, carrier frequencies and direction of arrivals of the detected busy bands. Here, reconfigurability allows the base station to select and digitize non-contiguous frequency bands by performing sparse sensing in temporal and spatial domain. Whereas intelligence allows the selection of desired frequency bands such that characterization failure does not occur. This demonstration has found significant traction both with academia as well as industry given the multitude of use cases in 5G requiring efficient sensing and spectrum characterization for enhanced system operation.

A real-time multi-bot system consists of a group of robots working together to accomplish a common task. Each robot in the environment is provided with its own set of sensors, communication modules, vision systems, and control systems. A robot in the multi-bot environment is given complete autonomy or partial autonomy or teleoperated based on the task. For a robot to navigate autonomously, they should be capable of knowing their own position and pose in the environment, I.e., localization. Localization is achieved by the process of Data Fusion. Data fusion is the process of combining the data from sensors that sense motion and sensors that represent the environment. For a robot, the data collected from its sensors are available only to itself. In a multi-bot system, the data collected from a single robot should be made available to all the other robots in the environment. Each robot collects the sensor data of its own and shares this information among all the other robots in the environment. The connectivity and exchange of data between individual robots is a key issue in a multi-bot environment. The multi-bot system performance and safety can be increased by high speed, low latency exchange of data between individual robots. Moreover, keeping a robot informed about others in their surroundings increases the knowledge and makes each robot take a global decision in the environment rather than local decisions. This experiment demonstrates the high-speed exchange of information between robots and quantifies the delay elapsed in it. This also proves ROS2 has good performance over ROS and best suited for the multi-bot system.

Motivated by the emerging delay-sensitive applications of the Internet of Things (IoT), there has been a resurgence of interest in developing medium access control (MAC) protocols in a time-slotted framework. The resource-constrained, ad-hoc nature of wireless networks typical of the IoT also forces the amount of control information exchanged across the network - required to make scheduling decisions - to a minimum. In a previous article we proposed a protocol called QZMAC that (i) provides provably low mean delay, (ii) has distributed control(i.e., there is no central scheduler), and (iii) does not require explicit exchange of state information or control signals. In the present article, we implement and demonstrate the performance of QZMAC on a test bed consisting of CC2420 based Crossbow telosB motes, running the 6TiSCH communication stack on the Contiki operating system over the 2.4GHz ISM band. QZMAC achieves its near-optimal delay performance using a clever combination of polling and contention modes. We demonstrate the polling and the contention modes of QZMAC separately. We use an Adaptive Synchronization Technique in our implementation which we also demonstrate. Our network shows good delay performance even in the presence of heavy interference from ambient WiFi networks.

In many cities in India, millions of commuters use public transit for traveling to various places in a city. Public transit offers an inexpensive way to travel which is crucial in a poor country like India. Public transit thus increases economic mobility and is therefore very crucial. However, unlike most developed world, the information regarding the arrival of transit as well as the general information about the possible routes of transit is not available which reduces the potential users of transit considerably. This leads to congestion and pollution due to the sub-optimal use of transit. An efficient and usable real-time trip planning feature is therefore a necessary pre-requisite to the adoption of the public transit in cities in India. The proliferation of smart mobile phones has made it possible for the commuters to access the real-time information about the transit. The natural question therefore is: how to show public transit information to the commuters in an ``optimal" way.

This paper presents MagnaSense, the first of its kind wireless computer 'mouse' that uses two magnetometers, and principles from magnetism and electromagnetic induction to achieve performance comparable to a traditional computer 'mouse', but with three degrees of freedom instead of two. We demonstrate MagnaSense to have the ability to draw various shapes as well as write text on the screen. Our prototype of MagnaSense is affordable, non-intrusive, handy and easy to use, with the user just requiring a magnet in his hand.