This paper presents VisIoT, a system that tracks the location of a wireless transmitter in IoT devices and displays it in the screen of an AR device such as smart glasses and tablet. The proposed system benefits existing IoT systems by enabling intuitive interaction between a user and IoT devices and further enhancing visualization of the data collected from IoT sensors. VisIoT achieves them through a combination of wireless sensing and camera motion tracking. By using the azimuth and elevation angles between the wireless transmitter and the camera-equipped mobile device, VisIoT can instantly identify the location of the IoT device from the camera image. This paper introduces novel azimuth and elevation estimation algorithms that leverage the phase difference of the signals from two antennas together with the tracked camera rotation. We prototype VisIoT using a tablet PC and a USRP software radio, and develop a software that tracks and visualizes the location of ZigBee nodes in real time. The evaluation results show that VisIoT can accurately track the nodes with the median position error of 6%.

Bluetooth Low Energy (BLE) is probably the best technological tool that we can harness today for studies on close human interactions. It has a wide deployment base (i.e., on smartphones), has peer discovery as an inherent protocol feature, does not require infrastructure (e.g., satellites or base stations) to operate, and sparingly uses energy that is good for extended monitoring. In this paper, we show that we can use the BLE peer discovery capability on smartphones to detect and monitor massive and dynamic encounters, which would provide valuable insights into many epidemiological or sociological phenomena. However, being designed for more leisurely interactions, BLE needs some stretching in order to be used in large-scale operations. Specifically, the protocol design is not optimal to rapidly discover hundreds of devices in the communication range, whereas dense crowds and mass gatherings are not unrealistic in city life. Moreover, if the crowd is dynamic, discovery becomes even more time-pressed because encounters should be recorded before churn. In this paper, we push the BLE technology with the requirements to discover hundreds of devices before co-presence expires, and to work continually over a typical smartphone charge cycle. Specifically, we investigate how we should modify the BLE protocol and how we should set its protocol parameters for this purpose. We show that with the proposed changes and configurations, we can accelerate the speed of discovery for massive and dynamic crowds by more than an order of magnitude compared to the case that we naively follow the guidance of the current BLE standard.

Platooning is nowadays one of the most promising applications for vehicle-to-vehicle communications. Platooning makes multiple vehicles travel as closely as possible to get the maximum driving efficiency. The problem here is that the view of the rear vehicle driver may be blocked by the front vehicle. In order to improve rear driver's safety and psychological stability, video streaming among vehicles aims to provide the front view of the platoon leader to rear vehicle drivers. In this paper, we first focus on measurement of realtime video streaming performance using IEEE 802.11p broadcast in the platoon. As a result, packet delivery ratio dropped to 48% in the worst case that the collision and hidden terminal problem coexist. To mitigate the frame loss, we use pseudo-broadcast that can recover frames by retransmission instead of broadcast. In addition, we employ Request-To-Send/Clear-To-Send whose transmission power increased by 5 dB to solve the hidden terminal problem. Consequently, we can prevent the frame loss and increase the packet delivery ratio up to 96.8%. Our proposal enables vehicle-to-vehicle communications to exploit a new method integrating characteristics of unicast and broadcast to solve this problem. Besides, our proposal can easily apply to existing devices by updating a device driver without any hardware chip level modification.

As autonomous vehicles loom as reality, and the vehicle communication starts to be enforced by law from 2020, protecting vulnerable road users (VRUs) using vehicle communication is receiving attention. The current vehicle-to-pedestrian (V2P) communication as stipulated by the standards such as SAE J2735 implies that it is the vehicles that take the responsibility for VRU protection. User devices are essentially beacons that transmit Personal Safety Messages (PSMs), and upon receiving PSMs, the drivers (or autonomous vehicles) take necessary measures to protect them. We, however, believe that the road users also need information about nearby vehicles to protect themselves from dangerous situations. Using other technologies than the standard Dedicated Short Range Communication (DSRC), there have been existing works for VRU protection. They use Wi-Fi or Wi-Fi Direct as replacements of DSRC. An automaker tested DSRC for VRU protection, but no technical detail has been presented. An important issue with the existing VRU protection proposals is that they are fraught with false alarms, which lowers the utility of the whole idea. Although one can come up with a highly precise collision prediction model, any such model will generate a huge number of false alarms, especially in urban environments. For example, if a pedestrian walks along a sidewalk well protected from the driveway, all passing vehicles will generate an alert to the pedestrian and vice versa. So our approach instead provides intuitive visual cues to the smartphone user looking at the screen, so that they can use their discretion to determine the level of danger for themselves.

Although Wireless Access in Vehicular Environment (WAVE) will be legally enforced from 2020 after the recent move by the U.S. Government [1], there is still an unresolved security issue. It is data plausibility, which is not addressed in any standard that comprises the WAVE framework. In particular, an attacker may forge false position values in safety beacons in order to cause unsafe response from startled receiving vehicles. The data plausibility is a longstanding issue for which various approaches based on sensor fusion, behavior analysis and communication constraints have been proposed. However, none of these completely solve the problem.

Smartphone magnetometer traces can be used to check if the owners moved in proximity. Using time-lagged cross-correlation of the traces, a fine-resolution judgement can be made within a few meters in any formation. The technique works indoors and outdoors, with no communication infrastructure, with less power and higher resolution than GPS, and with less privacy violation than beaconing. Research and practice on human interactions, such as epidemiology and sociology that need fine contact tracing between complete strangers, can harness the technique.

In the Internet of Things (IoT) era, smartphones are expected to frequently interact with IoT devices and even facilitate various IoT applications. Due to limited roles, energy constraints, etc., however, IoT devices may use mission-tailored or proprietary wireless protocols that smartphones do not speak natively. In this paper, we propose a novel approach to the wireless “language barrier” problem between the smartphones and IoT devices of the future. We first demonstrate that smartphones have become powerful enough to process software defined radio (SDR) for some known wireless protocols. Moreover, we show that the SDRs can be packaged as “apps” and be downloaded from app stores for OS-independent deployment. Second, we show different SDR protocols on the smartphone can concurrently run through a shared RF to serve multi-tasked applications on it as might happen in diversified IoT environments. For proof-of-concept, we implement a prototype architecture that has all the SDR logic and supporting middleware on an Android smartphone which uses a USRP as the simple RF-end. Finally, we demonstrate that IEEE 802.11p and IEEE 802.15.4 SDRs on a smartphone, respectively, communicate with a ZigBee sensor mote, a ZigBee smart lightbulb, and a commercial Wireless Access in Vehicular Environment (WAVE) device, concurrently.

Recent advances in smartphone processing power have opened the possibilities for them to act as the processing component of software-defined radios (SDRs). For low-power sensor network systems using various communication protocols, this means that smartphones, when equipped with an SDR, can be their system management end-devices, (potentially) without the need for external communication modules. Nevertheless, the high processor and energy usage overhead of SDRs remains a major technical barrier that blocks the practical adoption of smartphone-based SDRs. In this work, we show that implementation flexibility at the software can relax this overhead. Specifically, we show, using an implementation of the low-power listening (LPL) Medium Access Control (MAC), that software improvements have the potential to significantly reduce the operational overhead of SDRs. Moreover, we show that implementing packet reception filters can help further reduce the performance overhead without sacrificing application-level message exchange qualities. Empirical results with a smartphone-based SDR suggest that by combining LPL with packet reception filters, the processing and energy overhead can be reduced by two to three orders of magnitude. We not only see this as a chance to practically realize smartphones as a wireless sensing system controller but also believe that the experiences with practical smartphone-based SDRs can provide guidelines for future wireless protocol and low-power radio designs that are suitable for mobile computing environments.

In the IEEE Wireless Access in Vehicular Environment (WAVE) environment, periodic beacon messages enable proximity awareness that helps prevent collisions. One of the barriers that hinder the beacon delivery is congestion, which means that the amount of beacon traffic exceeds the Dedicated Short Range Communication (DSRC) channel capacity. In this paper, we propose a scheme for vehicles to independently adjust the beaconing rate based on the estimated neighbor vehicle population. Unlike previously proposed works, the proposed scheme does not need cross-layer information such as channel busy ratio (CBR) in order to achieve significant beacon throughput. We demonstrate through extensive simulations that this scheme significantly improves the beacon throughput.

In this paper, we explore the possibility of using smartphones as WAVE devices. When it is expected to take more than a decade from now to deploy the WAVE technology in full scale, smartphones running the WAVE protocol stack can bring the benefit of the technology earlier. In particular, we design and implement the lower layers of the WAVE stack in software defined radio (SDR) on smartphone platform and test its vehicle-to-vehicle (V2V) performance in the real driving scenarios. We also investigate the performance in the vehicle-to-pedestrian (V2P) communication context.

In this demo, we showcase the first software defined radio (SDR) implementation that runs on today's smartphones. Using the SDR, the smartphones are shown to talk to real IEEE 802.15.4 devices such as sensor motes or Phillips Hue (TM) lightbulbs that otherwise they cannot natively communicate with. Furthermore, we make the SDR available as downloadable software ("app") on Google app store, so that anyone may freely download, use, and purge on his or her smartphone, independently of OS upgrades. Detaching SDR from OS allows almost immediate deployment of wireless rotocols, and only on the phones that do need them. By enabling smartphones to speak non-native protocols in this manner, smartphone vendors will be able to support a wide range of wireless protocols without investing separate hardware and real estate in their devices. A promising application area for this concept could be Internet of Things (IoT), where protocols are diverse, typically low-speed, and not well supported by today's smartphones. Therefore, we believe that the smartphones with SDR will become a strong enabler or facilitator of many interesting applications in the IoT environment. We also believe that the concept of wireless protocol as a smartphone app will accelerate wireless protocol design-test-deployment cycle, catalyzing wireless protocol evolutions on smartphones.

Designing and distributing effective vehicular safety applications can help significantly reduce the number of car accidents and assure the safety of many precious lives. However, despite the efforts from standardization bodies and industrial manufacturers, many studies suggest that it will take more than a decade for full deployment. We start this work with the hypothesis that smartphones may be suitable platforms for catalyzing the distribution of vehicular safety systems. Specifically, smartphones connected to their respective cellular networks can report sensing data to back-end application servers and exchange safety-related messages. This paper first evaluates the performance of the vehicular ad-hoc networking standards and the hardware platforms that implement them. Next, we perform empirical evaluations on the performance of cellular networks to confirm their applicability in vehicular networking. Based on our observations, we present the VoCell application development framework. VoCell, comprehends a set of components that eases the development of smartphone applications for vehicular networking applications. Using VoCell, developers can easily access internal and external sensing components and share this data to servers. We present a number of example applications developed using VoCell and evaluate their effectiveness in local and highway environments using a pilot deployment. We envision that VoCell can act as a building block for enabling new smartphone-based systems for vehicular networking applications.

Today, Radio Frequency ID (RFID) technology is adopted in many applications such as asset tracking, supply chain management, manufacturing, retailing, payment systems, security and access control [1]. In this poster, we consider a novel application that we call city tagging, where the tags are attached or embedded in buildings and immovable structures to assist localization and landmark annotation [2].

The IEEE 802.11 wireless LAN (WLAN) is a time-tested technology, but it is still evolving towards even higher speeds and richer features. For multi-room IPTV delivery, where multiple IPTVs are fed from a main set-top box (STB), the IEEE 802.11 WLAN is an attractive choice for wirelessly connecting the STB and the IPTVs. In this paper, however, we first show that both the standard 802.11 unicast and broadcast/multicast delivery mechanisms have efficiency and reliability issues when they are applied to the multi-room IPTV delivery. In order to resolve the issues, we propose to use so called the pseudo-broadcast, where a unicast transmission is promiscuously received by multiple receivers. By dynamically changing the unicast destination based on the 802.11k measurement, the scheme also minimizes losses experienced by the promiscuous receivers. The scheme can be implemented without any change in the 802.11 standard, and provides a cost-effective solution to high-reliability and high-efficiency multi-room IPTV delivery.