<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

With an alarming increase in obesity levels, even among children and adolescents, there is a need to take steps for increasing their motivation and overall physical activity levels. This paper proposes a way for concerned authorities in a school, to easily keep track of each student's physical activity during school hours and give feedback accordingly. The system uses a portable pedometer that includes a MPU6050 sensor module that uses an accelerometer and gyroscope to collect movement data from each student and stores it, via Wi-Fi communication on to the Thingspeak server. The system implements a k-NN algorithm that classifies the data for each student into activities of sitting, walking, running and cycling. The results of the analysis and feedback for each student are accessible through a web portal, hosted locally on a server located in the school premises. © 2018 IEEE.

Computer Science and Engineering

(SoE) School of Engineering

INDICON 2018 - 15th IEEE India Council International Conference

Actiotracker: A Smart Pedometer for Monitoring and Analyzing Physical Activities of School Children

In densely populated metropolitan cities, people spend an average of 45-150 minutes inside a vehicle commuting to their workplace. Most of these travelers often experiences short term health conditions like drowsiness, breathlessness, discomfort and headache. Many accidents have been reported due to drowsiness while driving. There has been considerable increase in the number of death/choking cases reported due to CO 2 buildup inside the vehicle. Even though Vehicle Indoor Air Quality is an important parameter, the general awareness about it is very low, and only few high end new models of automobiles have indoor air quality sensing systems, with limited capability. This paper attempts to use a sensing system that can be retrofitted in any old or new vehicle to measure the CO 2 level inside the vehicle and use this sensed data to perform statistical and stochastic analysis of the growth pattern of CO 2 inside the vehicle chamber. © 2018 IEEE.

Proceedings of IEEE Sensors

Predictive Modelling of In-Vehicle CO 2 Concentration Using Sensor Data Analytics

IoT devices generate data at a remarkable speed which requires near real-time processing. Such need has inspired a new computing paradigm that advocates moving computation to the edge, closer to where data is generated for ensuring low-latency and responsive data analytics. This paper aims at monitoring indoor environment parameters inside the classroom in real time and estimate the occupancy of that room based on the collected data This is done by measuring different environmental parameters like temperature, CO2 etc. and then by performing regression on the collected data. For the purpose of real time monitoring an android application is used which uses MQTT for communication with the edge node. The estimation is then verified against the actual attendance in the classroom at that duration and it gives accuracy between 90\%-95\%. © 2018 IEEE.

14th International Conference on Information Processing: Internet of Things, ICInPro 2018 - Proceedings

Occupancy Estimation Using Sensor Data Analytics

Vehicle Indoor Air Quality (VIAQ) is a very important parameter that we often tend to ignore in our daily driving. VIAQ can worsen due to build-up of carbon dioxide (CO2), carbon monoxide (CO) and other harmful gases emitted by vehicles. Poor VIAQ can lead to short term health conditions like drowsiness, breathlessness, discomfort and headache. Drowsiness while driving is a predominant health condition that leads to large number of accidents and deaths all over the world. Standard equipment of air intake and recirculation in both low end and high end cars do not completely support pervasive maintenance of VIAQ. Due to unavailability of miniaturized sensors, a general purpose solution to this problem was rarely studied and addressed. In this work, we propose a novel mobile sensing system to monitor and understand change in VIAQ. Our mobile sensing system is general purpose, built by using an Android Smartphone and a mobile sensor, is independent of car age and model, and monitors VIAQ at all times. © 2016 IEEE.

2016 IEEE Annual India Conference, INDICON 2016

Real time in-vehicle air quality monitoring using mobile sensing

Energy efficiency have always been a priority while designing wireless sensor networks. Introduction of mobile agent technology in wireless sensor networks for collaborative signal and information processing has provided the new scope for efficient processing and aggregation of data. Mobile agent based distributed computing paradigm offers numerous benefits over the existing and commonly used client/server computing paradigm in wireless sensor networks. Mobile agent performs the task of data processing and data aggregation at the node level rather than at the sink, thus, eliminating the redundant network overhead. One of the most important issues in mobile agent based paradigm is planning of an itinerary for agent traversal. In this paper, we have proposed a dynamic mobile agent based data aggregation approach that takes into consideration energy efficiency, network lifetime, end to end delay and aggregation ration while making the decision for migration of agent in multihop sensor network. As our approach focuses on finding the most informative route by traversing comparatively less number of nodes consequently mobile agent takes less time to return to processing element, thus, exhibiting lower delay. © 2016, Springer Science+Business Media New York.

World University root node

Wireless Personal Communications

Energy Efficient Data Aggregation in Mobile Agent Based Wireless Sensor Network

Mobile agent based computing paradigm has an edge over the existing client/server computing paradigm. With the development of mobile agent based wireless sensor networks; various new resource-efficient potentials have been identified for data processing and data aggregation applications. These approaches either use a single mobile agent or multiple mobile agents for data processing in the network. The foremost issue in mobile agent based paradigm is to plan a route for agent traversal. This paper is an effort to present a mobile agent itinerary planning approach using concepts of information gain and accuracy for efficient data aggregation. © 2015 IEEE.

12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015

Dynamic mobile agent itinerary planning for collaborative processing in wireless sensor networks

Environmental monitoring using external and Smartphone-interfaced wireless sensors has been widely used in the past. The roadblocks start emerging when we use on-board sensors in off-the-shelf Smartphones to estimate context aware environmental parameters like ambient temperature, humidity and atmospheric pressure. In this work, we evaluate the sensitivity and accuracy of the on-board ambient temperature sensor under various circumstances and measure its performance against standardized weather monitoring equipment. Additionally, we identify the roles of several internal and external factors that affect the temperature data. Such an investigation is motivated by the need of pervasive temperature sensing to power Smart HVAC environments and for weather crowdsourcing. Our experiments reveal that while the on-board temperature sensors have great potential, using them for large scale data collection still requires significant work. © 2015 IEEE.

Life Sciences

(SoNS) School of Natural Sciences

2015 7th International Conference on Communication Systems and Networks, COMSNETS 2015 - Proceedings

Contextual sensitivity of the ambient temperature sensor in Smartphones

Social networking applications are changing the way people communicate with their peers and family. Social networking applications have several features that help in connecting one to another, from finding old friends to browsing for new friends and contacts. To harness the true power of social networking, sometimes it may be important to seamlessly identify and connect individuals who are geographically nearby with similar interests at a given time. In this work, we develop and discuss a pervasive and context-aware social networking system in a mobile environment that is able to report the presence of like-minded individuals in real time based on user's location. We discuss how our system computes closeness between two individuals and develop an application to test its efficacy. © 2014 IEEE.

2014 IEEE International Conference on Advanced Networks and Telecommunication Systems, ANTS 2014

PECSNET: The next generation pervasive and context aware social network

Mobile agents in wireless sensor networks provide many advantages in comparison of conventional client/server architecture. Mobile Agents follow code to data approach and thus perform the task of data aggregation at the nodes rather than at the processing element. This approach reduces in-network data transmission, thus improving bandwidth usage and prolonging network lifetime. Use of multiple mobile agents instead of single mobile agent allows the task to get completed in a cooperative manner. In this paper, we present a multi agent solution for data aggregation using source grouping along with tree based ordering. Extensive simulations have proved better results in terms of energy consumed and latency in comparison of other approaches. © 2014 IEEE.

Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014

Multi-Agent data aggregation in wireless sensor network using source grouping

Mobile Agent (MA) based distributed computing paradigm offers numerous benefits over the existing and commonly used client/server computing paradigm in wireless sensor networks (WSN). MA performs the task of data processing and data aggregation at the node level rather than at the sink, thus, eliminating the redundancy network overhead. One of the most important issues in MA based paradigm is planning of an itinerary (route) for MA traversal. In this paper, we present a centralized MA itinerary planning approach using Grey Relational Analysis (GRA). The residual energy, migration cost and information gain are the factors considered for the next node selection of the itinerary, and GRA is used for finding out their importance level and determine their weighted values. Simulation results exhibit that the GRA based proposed approach performs better than the previously existing approaches. © 2013 IEEE.

2013 6th International Conference on Contemporary Computing, IC3 2013

Itinerary planning using grey relational analysis for mobile agent based wireless sensor networks

Mobile Agent (MA) based computing paradigm offers many advantages over the existing and widely used client/server computing paradigm in wireless sensor networks (WSN). MA performs the task of data processing and data aggregation at the nodes rather than at the sink, thus, eliminating the redundancy in the sensory data. One of the most important issues in MA based paradigm is planning of an itinerary (route) for MA traversal. In this paper, we present a centralized MA itinerary planning approach using Analytic Hierarchy Process (AHP). The remaining energy of the node, migration cost and information gain are taken into consideration for the selection of subsequent node of the itinerary. AHP is used for determining the weights to each of the above parameter, thus, simplifying the task of decision making. Simulation results exhibit that the proposed approach lowers the task duration and energy consumption of the network. © 2013 IEEE.