Tag: smart phone

Smart Solutions for Smarter India

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Students from IIT Kharagpur have devised unique solutions for smarter & safer industrial operations ranging from detecting counterfeit currency through a mobile app, to nuclear radiation tracking through wearable sensors, to VR based human resources training at a thermal power plant.

Fake Currency Indian Notes (FCIN) have plagued the country for decades leading to not only economic losses for the country but also as the source of funds of various illegal activities even leading to breach of national security. The country has witnessed a mega initiative like demonetization in 2016. The government has also been promoting digital financial transaction which would minimize the circulation of FCIN. The banks and retail traders who manage institutional high-volume cash transactions have adopted various measures to detect FCIN. But how would an end consumer detect such a currency note? Though there are set guidelines by the Reserve Bank of India, an untrained eye can easily falter.

A group of six students from the Dept. of Computer Science and Engineering IIT Kharagpur have developed the code for a smartphone application to address this issue. T.Y.S.S.Santosh, Satish Kumar Reddy, Vipul Tomar, Sai Krishna, Drishti Tulsi and D V Sai Surya have developed an image processing application which can detect counterfeit currency. The application which can be installed on smartphones can be used by people at various touch points thus reducing the chances of fraud. Explaining the mechanism, T.Y.S.S.Santosh, the group leader said,

a user can upload a currency note image and the mobile app would verify its authenticity using 25 features extracted from the front and rear side of the currency note. In case of detection of a fake note, the user will also be notified of the failure checkpoints.

In another innovative project,  the Department of Atomic Energy gave the challenge of resolving the occupational hazard of people working in the domain of nuclear-powered device. The students were asked to develop a solution for visualising and localising a 3D radiation source along with its size, shape and orientation, given the data on spatial dosage. The 6-member student team from IIT Kharagpur, comprising of Lakshay Bansal, Ch V Sai Praveen, Aditi Kambli, Rajshekhar Singhania, Ayush Mohanty, Kaustubh Agrawal, proposed a solution based on Boltzmann Transport Equations dealing with the flow of heat in fluids from hotter regions to colder ones. The students solved the reverse Boltzmann Transport Equations using the dataset for a given area to estimate the source location.

This solution is well suited to occupational workers carrying wearable sensors detecting radiation dose data. The sensors can pinpoint the location of radiation leaks in nuclear plants and refineries. The solution can also find application in medical radiation therapy or radiotherapy as part of cancer treatment to control or kill malignant cancer cells

– Lakshay Bansal, the team leader.

Another team from the Institute has developed a virtual reality-based application for the training and skill development of the workers through interactive drill based training. The solution is an interactive virtual reality environment of a thermal powerplant with simulations and guides to help operations, maintenance and performance of complex procedures in an efficient and error-free manner.

Our solution offers an economical, intuitive and gamified version of worker training through level wise learning approach. It provides a full set of interactive drills to perform along with quality assessment metrics that could be used by the supervisors to assign different jobs to workers.

– said Rohit Jain who led the team comprising Suresh Gandhi, Sumeet Aher, Ishan Bangia, Sunil Patidar, Ayushi Shakya from IIT Kharagpur.

The students proposed these solutions in the recently concluded Smart India Hackathon 2019 winning some of the top prizes in the nationwide competition held by the Ministry of Human Resources Development, Govt. of India

IIT Kharagpur also hosted the software edition of the Grand Finale of SIH 2019. The prize winners developed codes targeted on smart education solutions. Team CodeLagom developed a wearable Android IoT device for facilitating the education of differently-abled people with vision and hearing impairment. Books in PDF can be uploaded on the web platform of the device which can thereafter be streamed on the wearable device in voice and visual modes. Team LeetCoders wrote the code for a LAN-enabled smart board for classrooms which can detect handwriting in both Hindi and English languages and broadcast the content to connected boards in other classrooms. It can also solve arithmetic equations and saves notes in PDF. The third team, The Creeping Spiders, developed a smart attendance system through facial recognition by means of random image clicks in a classroom or office environment.

Smartphone App to Aid Smoking Cessation

Smartphone applications in the present times are the popular source of information on market intelligence. In the last decade, these gadgets have been revolutionizing the consumer world by replacing our wallets and bringing services such as cabs, restaurants, shops, IoT based smart homes at our doorsteps. These are also contributing to our fitness regime. But smartphones can give a lot more insights, they can tell what we are doing at the moment, our habits and the associated health hazards. This is what researchers at IIT KGP have confirmed through their latest innovation.

A research team led by Prof. Ram Babu Roy at IIT KGP’s Rajendra Mishra School of Engineering Entrepreneurship (RMSoEE), has developed a prototype of sensor-based activity tracking kit which can monitor the activities in daily living. Further, a Smartphone-based application is under development which will analyze the tracking kit data and send alerts for an unhealthy lifestyle and suitable recommendation. The innovation is a sensor-based technology for automated recognition of addictive and depressive behaviour.

While India is reaching a critical threshold for killer diseases like cancer and depression, there is an emerging need for a shift from sick care to preventive care. This issue can be addressed at a faster rate through e-healthcare considering the inadequate availability of professional caregivers and medical practitioners.

“The scenario led us to explore the most commonly used gadget and develop the much-required technology which can be used for providing interventions in near real-time via mobile app to promote cessation from addictive habits,” remarked Saurabh Singh Thakur, a research scholar at IIT KGP RMSoEE.

The technology is capable of producing a daily activity chart based on body movements especially of the hands and predict daily functions such as eating or drinking water or behavioural tendencies such as smoking or consumption of alcohol. The application can also monitor call and message logs and internet usage on the smartphone and alert the user or the caregiver regarding cell phone usage. Prolonged usage data would indicate poor sleeping habit thus predicting possible health hazards.

“We did a pilot study over a period of time capturing data on activities of daily living with the help of a mobile app developed for android phones. The different activities captured are a marker of various physiological and psychological health. The data collected was dependent on the time of the day when it was captured thus demarcating the normal and abnormal activities. Further, data analysis is being carried out to identify various behavioral activities and patterns to do behavioural profiling of individuals. This could lead to enabling of personalized e-healthcare services through a smartphone,” said Prof. Ram Babu Roy, who is leading this innovation at IIT KGP RMSoEE.

The activity tracking kit has been developed using a 6-axis inertial sensor along with a heart rate sensor which could be worn on the wrist. A pilot study was conducted with four participants. Their hand movement pattern was recorded for around 5 minutes for smoking and non-smoking intervals each, using this kit. Preliminary analysis of the data showed that there exists a periodicity in the data during the smoking episode. During the non-smoking interval, the sensor signals are random and do not exhibit such periodicity.

Further data collection with a greater number of participants in different environments, data pre-processing, analysis, training, model generation, and testing is under progress. The research team collected GPS data as well for locational information and physical movement. There is a correlation between physical activities during the day and psychological health. Thus, such data analysis would further help in strengthening the mental health and wellness of the user.

The need of such a technology can be more emphasized at the wake of the reports by Indian Council of Medical Research (ICMR) and National Mental Health Survey (NMHS). While according to ICMR, new cancer cases or its incidence in India are estimated to grow by 25% by 2020, NMHS 2015-16 reports that every sixth person in India needs mental health intervention of some sort.

The prototype developed at IIT KGP is initially focused on smoking habits. However, the research encompasses the scope of predicting depressive behavior as well. The team has published several peer-reviewed papers in international journal and conferences of repute. They are working towards filing a patent for further commercialization of the product.

“At the Rajendra Mishra School of Engineering Entrepreneurship, we encourage entrepreneurial minds of the engineering students. It is the first school of its kind in India and we focus on incubating innovations into start-ups. Considering the field reports and further test results and preferred career choices of the innovators, such innovations are quite capable of creating new markets,” affirmed Prof. Partha Pratim Das, Head, RMSoEE, IIT KGP.