To support fast ingestion and fast query processing, modern data stores handle incoming data in an out-of-place fashion. Deletes in such data stores are realized logically by inserting additional metadata. We highlight that all out-of-place data stores treat deletes as second class citizens, and are not designed to efficiently realize deletes without hurting performance. The objective of this project is to design data stores that offer optimal performance while ensuring timely and persistently deleting data from modern out-of-place data stores.

UPDATE

[Jun 2020] The website for Lethe is now online at here.

With the emergence of the Internet of Things (IoT), an increasing need for preserving the privacy of personal data has been realized. In this context, the EU has recently published the general data protection regulation (GDPR), which ensures strengthening of the privacy rights of the data subjects concerning their personal data. The objective of this project is to highlight the importance of having a holistic solution aimed towards the enforcement of the GDPR. As a first step towards the enforcement of the GDPR, we outline the research challenges in facilitating the erasure of data as per the right to erasure, and propose a set of envisaged solutions to work through the challenges.

This project relates to the development of a Wireless Body Area Network (WBAN)-assisted "blind" cloud computing framework to enhance the existing ambulatory healthcare system without having extensive infrastructural dependence. As per the traditional healthcare techniques of the country (India), the diagnosis of a patient commences only after s/he is admitted to a medical unit or hospital. Thus, in cases of extreme criticality or medical emergency, the patient often undergoes tremendous inconvenience which may even be fatal. The proposed invention aims at introducing a novel ambulatory healthcare system coupled with the recent technological advancements. The idea behind this project is to provide majorly automated, remote, and ubiquitous ambulatory healthcare services in real-time.

After getting into an ambulance, a patient would be made to wear a set of easy, light-weighted, and convenient wireless body sensor nodes which would form a WBAN, and would instantaneously initiate the capturing the patient’s physiological data. These data would be fed to remote cloud servers in real time from where it would undergo a perfunctory analysis. To enhance the precision of the analytics, the invention envisions gathering a real-time medical history of the patient through a simple, form-based interface (with assistance from a paramedic). Based on the data criticality and medical history, voice or text-based feedback directives will be delivered at the patient’s end and will be executed by the paramedic within the ambulance.

The invention is strongly dependent on cloud computing technology as the cloud servers serve as the primary hubs of storage and computation of the system. However, to address the issues related to privacy, anonymity, and confidentiality of data within the cloud, the invention proposes to develop a completely “blind” cloud platform. The goal is to take advantage of the enormous computing and storage abilities of the cloud servers by maintaining data anonymity simultaneously. To preserve the privacy of the medical data, we propose an intelligent method to mask the identity of the patients, i.e., the users of the system, and thereby, obtaining unidentified data for storage and analysis. We also propose a parallel method to be executed within the non-cloud servers for efficient and lossless identity management and retrieval.

UPDATE

[Jan 2017] Website of AmbuSense is now live and can be accessed at this link.

[Dec 2016] Second phase of clinical trial was successfully conducted at All India Institute of Medical Sciences (AIIMS), Bhubaneswar involving both emergency patients and patients admitted in ICUs.

[Apr 2016] First phase of clinical trial was successfully conducted at B. C. Roy Technology Hospital, IIT Kharagpur which involved more than 25 patients.

In this project, we developed a seamless healthcare system that would allow remote and ubiquitous monitoring of patients’ health continuously across the clock. This system thrives on advanced wireless communication technology with different physiological sensor nodes as active participants. The sensor nodes mounted on a patient’s body (using patches, bands, or vests) sense different physiological stimulations, and subsequently transform the same into digital readings. The different nodes, which are responsible for measuring different physiological parameters of the patient are connected to a common hub, and together they form a wireless body sensor network (WBAN).

The proposed system also acquires, in real-time, the raw physiological data from multiple such WBANs (corresponding to multiple patients), and sends the same to a dedicated health cloud framework through a middleware. The cloud infrastructure is responsible for analyzing the raw data without incurring significant processing delay, and providing immediate, on-demand medical support through seamless, location independent procedures. The health data analytics are continuously executed on the data to detect any unusual health condition. Detection of irregularity, if any, is notified immediately to the patient's concerned medical team and family. The healthcare teams also analyze the causative factors behind the abnormality and provide some valuable medical suggestions and feedbacks to the respective patients via the middleware.

This project relates to the development of the Big-Sensor-Cloud Infrastructure (BSCI) that immensely enhances the usability and management of the physical sensor devices. Traditional Wireless Sensor Networks (WSNs) are manufactured in a proprietary, vendor-specific design, and cannot handle application switching dynamically at runtime due to the presence of monolithic kernel. Sharing of data is also non-trivial, as the WSN owners generally do not want to share their data to an external user in order to maintain security. Consequently, the renderability of WSNs is almost infeasible to people/organizations that do not own a network of their own. Thus, in the existing system, WSN-based applications are inaccessible to the naive-users or common people who do not own physical sensor devices. Of late, sensor-cloud infrastructure has been viewed as a substitute for traditional WSNs. However, with the increasing growth in the velocity, variety, and variability of data, the management becomes a serious concern and difficulty, and existing systems are not able to capture, analyze, and control the data efficiently, in real-time.

The BSCI is a distributed framework for “big” sensor-data storage, processing, virtualization, leveraging, and efficient remote management. The methods of the proposed BSCI are persuasive as they are equipped with the ability to handle “big” data with enormous heterogeneous data volumes (in zettabyte) generated with tremendous velocity. The framework interfaces between the physical and cyber worlds, thereby acquiring real-time data from the physical WSNs into the cloud platform. The primary components of the BSCI are the Repository Server, and the Cloud server. Within the Repository server, the unstructured raw data are acquired, virtualized and segregated into virtual sensors and virtual sensor groups as per the end-users’ application requirements on-demand. The data are further channelized to the respective Virtual Machines (VMs) that reside within the Cloud server. The Cloud server component structures the data in a distributed manner within every VM, using unique real-time processing algorithms and delivers the same to the end-users as a simple service – Sensors-as-a-Service (Se-aaS).

BSCI completely maintains and manages the data and the metadata internally within its database. Multiple organizations with heterogeneous demand can be successfully served with Se-aaS through BSCI. From a user-perspective, BSCI is highly convenient as the users are completely abstracted from the underlying complex processing logic. This allows the naive users to envision the typical hardware sensor devices as simple accessible services like electricity, and water.

UPDATE

[Nov 2014] The project was ranked among the top 9 in the 2014 IEEE ComSoc Student Competition “Communications Technology Changing the World” organized by the IEEE Communications Society.

Video surveillance is a rapidly evolving technology that deals with the security issues of places that need protection. The principal goal of the project is to provide a secure and reliable video surveillance system that assists in real-time vigilance and monitoring of activities within a boundary. The system developed supports real-time viewing, transmission, monitoring, recording, and management of video streams. Upon detection of an intrusion, the system generates an alarm (locally) and sends alert messages to the concerned authorities. Development of this prototype system is based on the principle of motion detection through background and foreground classification. The proposed system also allows for retrieval of previous records on-demand (for any given date and time) for review purposes.

UPDATE

[Dec 2012] The project was selected for the final round of the IBM The Great Mind Challenge (TGMC), 2011.