Priyanka Sinha

UbiHeld: ubiquitous healthcare monitoring system for elderly and chronic patients

Once the persons identity is established, the most important aspects of ubiquitous healthcare monitoring of elderly and chronic patients are location, activity, physiological and psychological parameters. Since smartphones have become the most pervasive computing platform today, it is only a logical extension to use the same in healthcare domain for bringing ubiquity. Besides smartphone, skeleton based activity detection and localization using depth sensor like Kinect make ubiquitous monitoring effective without compromising privacy to a large extent. Finally sensing mental condition is made possible by analysis of the subjects social network feed. This paper presents an end-to-end healthcare monitoring system code named UbiHeld (Ubiquitous Healthcare for Elderly) using the techniques mentioned above and an IoT (Internet of Things) based back-end platform.

Intelligent Social Network of Devices

People participate in social networks today whereas devices do not. Devices can generate a lot of data that can augment information in a social network. This chapter deals with how devices can contribute to a social network used by people. It describes the need for devices to detect user activity and allow other users to interact using that information, thereby creating an immersion of the real and virtual worlds. It discusses the enabling technology and associated problems in making a social network of devices work. Further, it outlines benefits to people participating in an intelligent social network of devices.

An interactive system using digital broadcasting and Quick Response code

This paper presents a novel method of creating synchronized interactive TV applications using Quick Response (QR) code, where QR code is used to tag the broadcasted TV content. The QR code is decoded at the receiver side to communicate with an Internet server for interactivity. The proposed technique can be used for both classical analog TV and digital TV. The method described here can also be applied on presently growing mobile TV and Over-the-Top (OTT) TV. It assumes Internet connectivity on the client. We present interactive TV based distance education as an example of a synchronized application using this system.

Using social network graphs for search space reduction in internet of things

In this paper, we explore reduction of search space in sensor data analytics using social network graph theory. Human centric social network allow graphical connect of individuals either based on familiarity or common intent. This facilitates people centric applications as they now operate on a much smaller data set. Extending this analogy to sensor networks, if sensors can be associated with meaningful social groups, it will reduce sensor data analytics and processing overhead for an application by a huge order. In this paper we explore how in Internet-of-Things sensors can be assigned to human beings who in turn are connected in social networks. Effectively in this way, sensors become part of a social network that results in a reduced data set for sensor data analytics.

City soundscape

This paper details an application to monitor noise in a city. The soundscape application involves capturing of audio data using users mobile phone, extracting the features and posting the same to the backend, running analytics on the same and then displaying it using a legend-based heat-map on a dashboard. This application can be widely used by the government to check noise pollution and to alert authorities of protests, terrorist attacks and other mass-destructible calamities.

Performance of Document Image OCR Systems for Recognizing Video Texts on Embedded Platform

Market demand for an embedded realization of video OCR motivated the authors to exert an attempt to evaluate the performance of existing document image OCR techniques for the same. Thus authors have tried to port the open source OCR systems like GOCR and Tessar act on an embedded platform. But their performance on an embedded platform shows that the character level and word level recognition accuracy is quite unacceptable for video text. This paper compares two such open source OCR systems on Indian TV videos and proposes some techniques that can be used to improve the recognition accuracy from 62% to 93%. Moreover the challenges of porting those codes on an embedded platform is also analyzed in this paper.

A methodology for GPS-based waterlogging prediction and smart route generation

This paper describes a system for predicting water logging prone areas in multiple routes. The approach is based on the theory that water tends to accumulate in low-lying areas and hence a route which contains more and bigger basins is more likely to behave worse on a rainy day. Using this basic principle, algorithms are formulated and applied to identify and quantify water logging zones on a route. To prove the effectiveness of the proposed system, the derived confidence scores for multiple routes given by the system are compared to judgements given by human commuters. A view of all possible routes along with quantified estimates of waterlogging confidence scores are rendered in Google map.