Mridula Singh

Janayuja: A People-centric Platform to Generate Reliable and Actionable Insights for Civic Agencies

With the proliferation of smartphone apps, social media, and online forums, modern citizens are actively discussing and expressing opinions about city related issues in open public forums on the web. This paper presents a people-centric platform, Janayuja, that can act as an effective conduit between residents and civic agencies, by collecting timely information from different online sources and providing actionable insights to the agencies on pressing city issues. In particular, we elaborate on four major components of the platform: (i) curation of reports from heterogeneous data sources; (ii) categorization of individual reports into relevant issues (e.g. bus breakdown) using suitable classification techniques; (iii) aggregation of related reports (in the spatio-temporal sense) to identify specific issues pivoted to distinct city locations; and (iv) verification of issues to ensure reliability of information being provided to the agencies. Janayuja is deployed for the largest public transport agency in Bangalore, India. Based on insights generated by Janayuja, the agency can better manage their current operations, understand and anticipate new requirements from commuters (e.g. for new bus routes) and, in turn, encourage greater usage of a public transportation system.

SenseX: Design and Deployment of a Pervasive Wellness Monitoring Platform for Workplaces

With the increasing number of desk jobs, workplaces have become the epicentre of several health risks. In this paper, we design and develop a pervasive wellness monitoring platform, SenseX, that uses a variety of devices and sensors to track physical activity level of employees in an organization. SenseX platform offers APIs which can be used by 3rd party applications to create services and applications, which can focus on specific interventions (e.g. to reduce prolonged sitting). We performed a real-world evaluation of the platform by deploying it in an IT organization for 6 weeks and observed longitudinal variations. We believe that SenseX platform helps in realizing the vision of “wellness as a service” in modern workplaces, enabling multitudes of different wellness services, which will be a key for sustained adoption of wellness programs.

Mauka-mauka: measuring and predicting opportunities for webcam-based heart rate sensing in workplace environment

Prolonged sitting and physical inactivity at workplace often lead to various health risks such as diabetes, heart attack, cancer etc. Many organizations are investing in wellness programs to ensure the well-being of their employees. Generally wearable devices are used in such wellness programs to detect health problems of employees, but studies have shown that wearables do not result in sustained adoption. Heart rate measurement has emerged as an effective tool to detect various ailments such as anxiety, stress, cardiovascular diseases etc. There are pre-existing techniques that use webcam feed to sense heart rate subject to some experimental constraints like stillness of face, light illumination etc. In this paper, we show that in-situ opportunities can be found and predicted for webcam based heart rate sensing in the workplace environment by analyzing data from unobtrusive sensors in a pervasive manner.

Improving Urban Transportation through Social Media Analytics

Citizens tend to discuss issues in public forums, social media, and web blogs. Given that issues related to public transportation are most actively reported across web-based sources, we present a holistic framework for collection, categorization, aggregation and visualization of urban public transportation issues. The primary challenges in deriving useful insights from web-based sources, stem from -- (a) the number of reports; (b) incomplete or implicit spatio-temporal context; and the (c) unstructured nature of text in these reports. The work initiates with the formal complaint data from the largest public transportation agency in Bangalore, complemented by complaint reports from web-based and social media sources. Text data is categorized into different transportation related problems and spatio-temporal context is added to the text data for geo-tagging and identifying persistent issues. A well-organized dashboard is developed for efficient visualization. The dashboard is currently being piloted with the largest transportation agency in Bangalore.

On large throughputs in high density enterprise wireless LAN(s)

While the density of access points in enterprise settings has increased, the sharing of the spatial resource amongst links in 802.11 wireless local area networks remains inefficient. Conservative mechanisms based on a static carrier sense range (CSR) are used and are designed to avoid occurrence of interfering transmissions. Even when the CSR is adapted to allow interfering transmissions, it is with the goal of increasing spatial reuse, which may not translate to a larger network throughput. We formulate the network throughput optimization problem, which is to decide which links in a network must share in space (transmit data simultaneously) such that the network throughput is maximized. Links share in space by piggybacking on data transmission opportunities seized by another link using RTS/CTS as specified in the distributed coordination function (DCF) of 802.11. Sharing in space increases interference and hence reduces the PHY rate at which a link can send data. It also increases the opportunities a link gets to transmit data, however. The optimization problem is NP hard. A relaxation of the problem gives an upper bound on network throughput. We propose computationally feasible algorithms that achieve a significant percentage of the upper bound. Our network modeling and evaluation is restricted to 802.11 networks in which all nodes always have a packet to send and are within carrier sense range of each other. Networks with a high density of clients and AP(s) are shown, via simulation, to achieve large throughput gains (up to 400% for 25 clients and AP(s)), over standard 802.11.

RadioMap: fine-grained cellular coverage mapping in indoor environments

Poor signal quality results in frequent dropped calls, degradation of throughput, and high battery consumption. Coverage maps advertised by cellular operators are very abstract and provide coverage information for outdoor areas. In real-world, most of the cellular phone usage is reported indoors and therefore, call drops are more frequent in these environments. Aiming to provide seamless connectivity indoors, we develop a system RadioMap that uses sensing capabilities of a smartphone to create fine-grained cellular signal maps in indoor environments. These signal maps provide a low-cost and pervasive solution to the cellular operators for finding signal dead spots in indoor environments and accordingly, take rectifying measures such as installing signal boosters, etc.