Chandrasekar Vuppalapati

Building a Big Data Analytics Service Framework for Mobile Advertising and Marketing

The unprecedented growth in mobile device adoption and the rapid advancement of mobile technologies & wireless networks have created new opportunities in mobile marketing and adverting. The opportunities for Mobile Marketers and Advertisers include real-time customer engagement, improve customer experience, build brand loyalty, increase revenues, and drive customer satisfaction. The challenges, however, for the Marketers and Advertisers include how to analyze troves of data that mobile devices emit and how to derive customer engagement insights from the mobile data. This research paper addresses the challenge by developing Big Data Mobile Marketing analytics and advertising recommendation framework. The proposed framework supports both offline and online advertising operations in which the selected analytics techniques are used to provide advertising recommendations based on collected Big Data on mobile users profiles, access behaviors, and mobility patterns. The paper presents prototyping solution design as well as its application and certain experimental results.

The Role of Big Data in Creating Sense EHR, an Integrated Approach to Create Next Generation Mobile Sensor and Wearable Data Driven Electronic Health Record (EHR)

Mobile is increasingly ubiquitous. With 6.8 billion mobile subscriptions world wide, access anytime, anywhere through smart gadgets is now putting cheap and connected, mobile computing power in the hands of millions of consumers and healthcare practitioners. Mobile Sensors -- accelerometers, location detection, wireless connectivity and cameras -- offer another big step towards closing the feedback loop in personalized medicine. There is no more personal data than on the-body or in-the-body sensors. With so many connected devices generating various vital health related data, integrating these data points to Electronic Health Records not only provide more accurate picture of the patient but also helps to connect with the doctor. In this paper, we propose Sensor integration framework with Electronic Health Records (EHR). Finally, the paper presents a prototyping solution design as well as its application and certain experimental results.

AI Infused Fragrance Systems for Creating Memorable Customer Experience and Venue Brand Engagement

In today’s competitive business environment creating memorable experiences and emotional connections (Creating customer value through service experiences: An empirical study in the hotel industry. Tourism and Hospitality Management 18, no. 1 (2012): 37–53) with consumers is critical to win consumer spending and long-term brand loyalty [1]. Brands want their customers to be in pleasing subliminal scented (Robert Klara, “Something in the air,” http://www.adweek.com/brandmarketing/something-air-138683/ creation date: March 2012, access date: January 02, 2017) environments because, as research has shown, even a few microparticles of scent can do a lot of marketing’s heavy lifting, from improving consumer perceptions of quality to increasing the number of store visits. Hence, customer venues such as hotels, retail showrooms, casinos, hospitable and other captive audience places employ HVAC (Heating, ventilation and air conditioning) based scent diffusion system that delivers a seamless olfactory [2] experience to connect with consumers on a deeper emotional level, resulting in a more memorable experience. Current scent diffusion systems, however, use power hungry deployments and dispense periodically, without accounting social mood, geographic local etiquettes, venue-patron occupancy ratios and sudden changes in foot traffic numbers. Thus, resulting sub-optimal user experience that might lead to a poor brand engagement and could incur higher operational costs and thus reduce over all return on the investment (ROI). In this research paper, we propose an innovative approach to create artificial intelligence (AI) infused Fragrance Systems that improve venue experience and operational efficiencies through the application of data science, Big Data Technologies, Edge processing, Supervised machine learning and IoT Sensing. Our system combines pragmatic data science and machine learning algorithms with arty social and mood drivers, albeit data science computed, to create adaptive and artistic fragrance system. The amalgamation data science with human mood influencers is our formula to the innovation that we propose and present a prototyping solution design as well as its application and certain experimental results.

Adaptive Edge Analytics - A Framework to Improve Performance and Prognostics Capabilities for Dairy IoT Sensor

Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch or other devices instead of waiting for the data to be sent back to a centralized data store. The data collection merits for normal edge operations but limits for the handling of anomaly events and prediction of prognostics conditions. In this paper, we propose an innovative machine learning edge approach that extends Kalman filter for anomaly detection so as to (a) allow the edge to adaptively collect granular data when abnormal or anomaly data markers witnessed for prognostics and (b) relaxes the data collection frequency for normal device operation cycles. In summary, the adaptive edge analytics fine-tunes the data collection and analysis so that overall health and longevity of the device can be improved. The paper presents prototyping dairy IoT sensor solution design as well as its application and certain experimental results.

iDispenser — Big Data Enabled Intelligent Dispenser

With healthcare-associated infections (HAIs) in the U.S. accounting for an estimated 1.7 million infections and 99,000 deaths annually, reducing and preventing these infections is a top goal for healthcare facilities throughout the country [1]. Not only healthcare facilities, in other captive environments, for instance, ships and cruises, provide environment that may increase risk of infection. According to Minooee and Rickman [2], “Ships provide an isolated environment that may increase the passenger’s risk of infection if exposed to respiratory viruses. High attack rates of influenza, for example, are typically seen in closed settings such as cruises, military vessels, aircraft, and institutions.”The high rates of infection in captive areas are influenced by number of people entering and exiting the place. As per the research summarized by “Hospital infection control: reducing airborne pathogens”[3], the number of people entering and exiting provides a contaminant source. It’s known that the concentration of airborne bacteria is proportional to the number of personnel in the room. The amount of surface contamination is also related to airborne contamination from occupation and activity since these microbes settle continuously.” Fencl [3] suggests that the use of disinfection, to control infectious agents in healthcare settings, is one of its oldest and most cost effective ways to control airborne infection. Nichols [1], importantly, suggest that touchless dispensing solutions as an effective way to help reduce the spread of germs. In our view, with advent of machine learning and Internet of Things, combining automated & intelligent dispensing with touchless systems provides more holistic approach to control infection in healthcare and, more importantly, captive places such as hospitals, cruises, casinos, airports and other places.In this research paper, we propose an innovative approach to prevent spread of airborne diseases through the application of Big Data Technologies and IoT Sensing. Our goal is to cutting down the millions of dollars spent on infectious diseases, intelligent dispenser promises to keep hospitals smelling fresh soothing and disinfecting. The paper presents prototyping solution design as well as its application and certain experimental results.

CENSE: A Cognitive Navigation System for People with Special Needs

Mass Transportation provides people with access to education, employment and places in the community. However, navigating around public transportation for the visually impaired and physically challenged sections of society is a challenging task. With rapid proliferation of technology, there has been a pressing need to develop enhanced methodologies to help people with disabilities access public transportation. While there are many navigation systems, some of them leverage Global Positioning System (GPS) technology, which is useful in outdoor environments but is not effective in navigating indoor environments. Beacons are emergent sensors that are becoming popular for indoor positioning in malls and airports. They use Bluetooth Low Energy (BLE) technology, which is extensively supported by all modern day smartphones. In this paper, we propose a proof of concept (POC) for a mobile application which uses BLE beacons to provide assistance to people with special needs. This application would provide an easy to use voice interface for navigating inside stations, buses and trains. As a part of our research, we aim to use existing beacons on some regional transit centers and deploy new beacons. We plan to analyze VTAs (Valley Transportation Authority) ridership data to extract contextual data about the commuters current environment to provide commuter with cognitive solution and assistance during travel. The end goal of our research is to enhance the VTA travel experience for special need travelers in the San Francisco Bay Area.

Fortune, Albeit Digital, at the Bottom of the Pyramid - Big Data Powered Business Model for Internet Service Providers

The Internet has become an essential part of day-today business. Many personal and industrial business use cases assume the availability of perpetual Internet access for fulfillment. The access to the Internet, ironically, is expensive, given various tiered pricing models that Internet Service Providers (ISP) employ. In many developing economies, the availability of the Internet is very sporadic, or only can be afford by a few. The enablement of free Internet access, Wi-Fi access points, in developing economies is huge business opportunity for ISPs. This paper discusses ISP driven business model of proving free Internet.