SURF-IT Research Projects


Participants | Research Projects

The SURF-IoT program provides a unique 10-week summer research opportunity for UCI undergraduates to become immersed in research and applications related to the Internet of Things (IoT).

Calit2 faculty, students and research professionals with leading California technology companies conduct research in “living laboratories” focused on the scientific, technological, and social components related to the Internet of Things.

2016 SURF-IT Research Projects

The following faculty-mentored research projects are available during the 2016 SURF-IT Program. They are divided into their own unique areas of research. Select a link for an overview of the project, associated faculty mentors, project prerequisites, and related publications.

SURF-IoT Undergraduate Research Projects

    1) Augmented Reality IoT Devices Supporting Game-Based Stroke Telerehabilitation  

    2) Design of Implantable Ocular Micro Pressure Sensor for Continuous Monitoring 

    3) Developing a Code Search Tool to Help IoT Developers in Programming 

    4) Integration of Crowdsourced and Traditional Data for Route Analysis and Route Finding for Pedestrians with Disabilities 

    5) Marching Cubes Made Tangible 

    6) MediCom – Integrating Multimodal Mobile Health Monitoring Data to Improve Doctor-Patient Communication about Medication Adherence 

    7) Mining Instagram/Twitter for Plant Data 

    8) Proabot Flotilla - Flocking Autonomous Sailcraft for Oceanographic Research 

    9) TurtleBot with Qualcomm Snapdragon ARM CPU 

 Project #1:  Augmented Reality IoT Devices Supporting Game-Based Stroke Telerehabilitation
Faculty Mentor:  Professor Walter S. ScacchiComputer Science

Project Description:
Stroke is a leading cause of disability and death world-wide, with approximately 850,000 stroke survivors annually in the U.S. Of these stroke survivors, nearly 2/3 endure some level of motor control impairment or hemiparesis. Rehabilitating and facilitating improved recovery of motor control of patient arms and legs is a major focus of research attention. UCI is a national leader in this area, under the direction of Dr. Steve Cramer (Neurology, Anatomy & Neurobiology, UCI Medicine and UCIMC).

Stroke Telerehabilitation is the name given to therapeutic approaches that employ networked information and communications technologies to lower the cost of high quality stroke therapy care into patient's home, so as to enable more personalized and convenient therapeutic care. I have been involved in the creation and design of a first-generation game-based stroke telerehabilitation system (GBSTR) that is deployed in a multi-site, nationwide clinical trial now underway [6]. This system is innovative and transformative, and utilizes many IoT devices (sensors and controllers) as seen in Figure 1. Nine different kinds of devices are utilized and integrated using two Verve 1 units (not visible) sourced from (Verve 2 units are now available). In the proposed effort, we seek to develop and demonstrate a new second generation GBSTR (GBSTR 2.0) that simplifies and streamlines the patient user interface to the GBSTR though utilization of an AR interface that can observe and visually render virtual objects aligned with functional therapeutic devices with embedded IoT sensors, actuators, controllers or effectors.

Computer games provide a compelling mode of interaction and user experience for learning about complex domains of entertainment or STEM practice [1,3,4,7.8]. New digitally-based Internet of Things (IoT) sensors, actuators, controllers and effectors are becoming available at low-cost, and our interest it to integrate them as new kinds of interactive game play/learning experiences. Augmented Reality
(AR) and Virtual Reality (VR) represent new modalities for rendering user views and immersive interaction experiences that may represent potentially transformative ways for learning about complex systems, such as those found in advanced healthcare and medical research/education, connected to local/wide-area networks [5,6].

The GBSTR 2.0 is envisioned to (a) utilize physical, functional objects (e.g., safe items found in a household kitchen for meal preparation) in ways that enable more effective therapeutic experience and motor control neuroplasticity at a lower cost; and (b) whose efficacy is (favorably) comparable to the standard of care currently available from professional care givers working in high-cost speciality clinics. An initial AR system interface, separate from the GBSTR, has been prototyped to demonstrate the plausible efficacy of this approach, using one device (a hand-wrist constrained movement computer mouse) and a computer vision system for mouse tracking [2]. This is shown in Figure 2.

While the efficacy is promising, this prototype has no practical extensibility and has been observed to be quite complex to operate and sustain. We believe this AR system can be replaced with a new, simpler AR user interface platform (a mobile device) that can be integrated for use with the GBSTR, using an articulated arm mechanism to support the AR interface display. This arm avoids the need for the stroke patient to either put on an AR headset (which they could not do, and which may be a safety hazard for them), or to physically hold a mobile device to see virtual objects projected onto physical objects placed on the GBSTR 2.0 desktop. Such sensing may be further simplified by affixing common QR codes to the objects, since QR code recognition software is widely available. Other uses for IoT devices to be embedded within functional objects for stroke therapy will be specified in the project.

The AR user interface can be realized using new low-cost commercial technologies. The commercially available AR/VR software package from EON Reality Inc., called “EON Creator AVR” is available for mobile devices from Google Play (now for Android platforms) and Apple iTunes (for iOS platforms in 2Q16). Utilizing software such as this, the student(s) will be able to develop and/or demonstrate prototype AR/VR apps that can support an AR visual display interface that can be viewed using either a mobile device (least cost) or AR headset (if provided by the project mentor or third-party).

The overall project goal is to produce a working example of an GBSTR 2.0 that can employ functional objects with embedded IoT devices, that can also be physically tagged with QR codes, then viewed with virtual objects attached to user selected object-activities, that are experienced via an externally supported AR mobile viewing platform. Access to the GBSTR, IoT devices, and AR software/hardware will be provided for use by the student(s) by the project mentor and Dr. Steve Cramer.

Student's Involvement and Expected Outcomes:
The participating student(s) will be involved in the design, development, testing, demonstration and documentation for how to integrate new IoT devices for use within a GBSTR 2.0 prototype created for this effort. Expected outcomes entail acquisition and embodiment of new scientific knowledge acquired through the proposed project effort. The embodiment of the knowledge acquired will focus on the demonstration, documentation, and presentation of the design, prototype development and operational testing of two or more IoT devices that rely on AR sensed, effected, or controlled virtual graphic objects that can be rendered using a compatible, mobile AR platform (e.g., tablet or smartphone). These results can be produced through a ten-week Summer project based on prior experiences with undergraduate and high school students that I have recently mentored [1,8].

Prerequisites: Student eligibility:
Required skills or knowledge needed to participate include:
-Prior experience in developing computer programs using at least two different languages among C/C++/C#, Python, Visual Basic or Javascript
-Being prepared to describe and demonstrate computer programs that the student has previously developed in such programming languages (programs may have been developed for UCI coursework, projects, job-related, or personal interest)
-Experience in playing computer games of different genres (FPS, RTS, RPG, or Sim games)
-Reading, review, and being prepared to discuss at least three of the Recommended Readings and Related Materials listed below.

Desirable skills include:
-At least one year of coursework in either physics, chemistry, biology, earth systems science, health care, or engineering subject other than Computer Science/Engineering.
-Prior experience with model trains, slot cars, R/C vehicles, drones or digital toys
-Willingness to play and systematically evaluate computer games that are in someway related to manufacturing systems
-Desire to engage in research related to game-based smart manufacturing using AR/VR user interaction experiences and technologies.

Recommended Web sites and publications: 
   1. Lin, R. Yampolsky, M. Scacchi, W (2014). Making Learning Fun: An Analysis of Game Design in Science Learning Games, Institute for Software Research Technical Report, UCI-ISR-14-3, October 2014.

2. Mousavi Hondori H, Khademi M, Dodakian L, McKenzie A, Lopes CV, Cramer SC. (2016). Choice of Human-Computer Interaction Mode in Stroke Rehabilitation. Neurorehabilation & Neural Repair. 30(3):258-65. doi: 10.1177/1545968315593805.

3. Scacchi, W. (2010). Game-Based Virtual Worlds as Decentralized Virtual Activity Systems, in W.S. Bainbridge (Ed.), Online Worlds: Convergence of the Real and the Virtual, Springer, New York, 225-236.

4. Scacchi, W. (2015). Repurposing Game Play Mechanics as a Technique for Developing Game-Based Virtual Worlds, in K. Cooper and W. Scacchi,Computer Games and Software Engineering, CRC Press, Taylor & Francis Pubs. (2015).

5. Scacchi, W. (2015). Computer Games and Virtual Environments for Medical Education and Research. Presented at the Academy For Innovation in Medical Education (AIME), UCI School of Medicine, June 2015.

6. Scacchi, W. (2016). Game-Based Stroke Telerehabilitation, Presented at the US-UK Workshop on Serious Games for Health, Drexel University, Philadelphia, PA, March.

7. Scacchi, W. Nideffer, R. and Adams, J. (2008). Collaborative Game Environments for Informal
Science Education: DinoQuest and DinoQuest Online, IEEE Conf. Collaboration Technology and Systems,(CTS 2008), Irvine, CA 229-236, May.

8. Yampolsky, M. and Scacchi, W. (2016). Learning Game Design and Software Engineering through a Game Prototyping Experience: A Case Study, 2016 ICSE Games and Software Engineering Workshop, Austin, TX.:

 Project #2:  Design of Implantable Ocular Micro Pressure Sensor for Continuous Monitoring
Faculty Mentor:  Professor G.P. LiElectrical Engineering & Computer Science

Project Description:
Glaucoma, typically caused by increased intraocular pressure (IOP) in the eye, is the leading cause of blindness worldwide, affecting over 70 million people. One significant problem for glaucoma treatments is the inability to easily measure intraocular pressure to assess the performance of the therapy and health of the eye. There are no portable tools that can determine intraocular pressure. Thus, the patient’s only recourse is to visit an eye clinic on a regular basis to have a measurement made using a clinical tonometer. This project aims to develop a micro implantable sensor that may be used with a microstent and would allow continuous monitoring and electronic readout using a low power radio frequency circuit. This would enable the pressure to be monitored often using a portable electronic device such as a mobile phone, and thus serve as a mobile implantable edge device in IoT. A number of micro-implantable devices for monitoring IOP have been developed [1], which can be categorized into two types: active and passive. Active implantable IOP monitors utilize micro pressure sensors and custom circuitry as part of the implant. They receive their power through the use of an inductive coil which couples via low frequency radio to an outside source. These sensors provide high quality pressure measurements, but tend to be large, bulky, and pose the risk of introducing electronic materials to the inside of the eye. Passive implantable IOP monitors sensors utilize pressure sensors that do not require active electronics. In some cases, this involves the use of a resonant LC circuit that changes its resonance when the passive sensor moves, such as when a capacitive membrane is depressed. This can result in the response of a radio wave that is reflected off it. Accurate measurement of the radio reflection can provide an indirect measurement of the IOP without the need for active circuitry in the device itself [1].

The purpose of our research project is to develop innovative methods of providing continuous monitoring of the intraocular pressure within the human eye, using an implantable, microscopic sensing device. Such a device could provide continuous monitoring of pressure within the eye with non-contact readout from an external device that is placed near the eye. This kind of implantable device with noncontact readout is extremely difficult to produce. The purpose for this study is to explore mechanisms that can lead to a working micro-implant. This work will explore two strategies for monitoring IOP with an implant: (1) a microscopic microfluidic pressure sensor with integrated 3D antenna, and (2) a diffraction grating that indicates IOP through the diffractive scattering of infrared light. The study is explorative for both strategies, and should yield sufficient data to accurately assess the viability of each strategy. If a concept is deemed feasible, the study should provide guidance on engineering designs for prototypes. As part of this study, alternate approaches will also be explored, as these ideas are formulated.

Student’s Involvement and Expected Outcomes:

Students will be involved in the majority of the tasks of the project. Students are expected to design and build the testing and experimentation set ups in the laboratory for characterizing the engineering devices, assist in the fabrication of proof-of-concept devices, and perform experimental work to evaluate and characterize the fabricated devices. Through accomplishing these tasks the students would grow crucial engineering skills as well as learn the use of a broad range of engineering tools, such as CAD tools, microfabrication, microcontrollers, modeling and data analysis tools. The students would also have the opportunity to develop their soft skills by working in a diverse team tasked to accomplish a multidisciplinary research work involving engineering, human physiology and medicine.

Prerequisites: Students in biomedical and electrical engineering are welcome to apply. Students with previous research and/or design experience are preferred.

Recommended Web sites and publications: 
   Ivantis website:

 Project #3:  Developing a Code Search Tool to Help IoT Developers in Programming
Faculty Mentor:  Professor Chen LiComputer Science

Project Description:
Recently Internet-of-Things (IoT) development is springing all over the world. People can use phones and wearables to monitor their own and their families’ health conditions.
They can have different accessories to remotely control or automatically adjust various aspects of their house. Many businesses are actively participating in this trend to build IoT products.

Very often IoT developers face many difficulties when developing software solutions for hardwares. They need to deal with vague documentation, outdated examples, even no
available online resources. For both hardware and software programmers, lack of richness in documentations, tutorials, and examples is a huge issue. It can be really helpful to look at other people’s open source code to learn and solve problems.

Unfortunately, diving into a huge unfamiliar codebase and trying to find the code is challenging. To solve this problem, we plan to study how to develop a code search engine to help IoT developers search in large codebases. There was once a service called “Google Code Search” to help developers look for source code. Unfortunately the service was closed in 2011. There are other existing alternatives, but their search interface, user experience, and search results are unsatisfying. We want to study challenges related to performing efficient search on large number of source code packages.

Student’s Involvement and Expected Outcomes: W e are currently building TextDB, a text management system, that handles large amounts of text information. TextDB is the core of the project. Students are expected to get familiar with TextDB, and conduct research using this open source tool. The goal is to achieve efficient code search on a very large amount of data sets. Advanced features, such as keyword search, regex, ranking results, and removing duplicates, would also be developed. The student will work with other graduate students in the faculty group to conduct research and receive guidance.

Prerequisites: Students should have excellent academic records, be familiar with Java, compilers, information retrieval, and database techniques. They should also have strong desire to learn new topics and get things done.

Recommended Web sites and publications: 
   TextDB project:
   How google code search worked:

 Project #4:  Integration of Crowdsourced and Traditional Data for Route Analysis and Route Finding for Pedestrians with Disabilities
Faculty Mentor:  Professor Amelia ReganComputer Science

Description:  Project Description:
The number of mildly and significantly mobility-impaired pedestrians continues to rise as the populations in developed urban centers ages. This research project will develop ways to integrate traditional data on pedestrian routes with crowdsourced data in order to analyze the safety, comfort and security of urban pedestrian routes and in order to provide pedestrians and their caretakers and companions with information on routes based on their individual needs and any potential hazards contained in those routes. The project focuses on two cities of similar size, namely New York and London, each with populations around 8.5 million and each with older transportation infrastructure that does not lend itself to simple remediation schemes, even if resources were unlimited. The primary analytical tools employed in this project are multi-objective shortest path methods, which are well known and well tested, and the very recently introduced ”network lasso” model which is a new machine learning model for clustering and optimization on large scale graph problems. The research team includes a UCI computer scientist, transportation engineering faculty at two major New York City Universities, and the director (a social scientist) of the interdisciplinary Transport Institute at University College London. The team will be applying for collaborative research grants from the National Science Foundation, from foundations such as the AARP foundation, which specifically targets research reducing isolation of older Americans, and Google Faculty Research Grants, which encourage research on technologies to improve the lives of people with disabilities. In addition, our UK partner will be applying for research funding from Horizon 2020 or other related EU programs.

Research Focus:
In this section, we introduce the three main areas related to this research. Distributed convex optimization is the main technique that can be used to model large scale transportation engineering problems, because many of transportation problems are naturally in optimization forms, such as prediction problems which is modeled by using loss function for residual errors, resource allocation problems which arise in wireless sensor networks especially, and combinatorial optimization problems, like routing and scheduling problems. With the advent of new technologies like sensors, camera and other communication technologies, a large amount of data are being generated. Therefore it is an important challenge to manage the data generated by Intelligent Transportation Systems more efficiently. These days, the management of Big Data arises in all areas of transportation engineering. Machine Learning algorithms have been applied to different prediction problems in transportation engineering. However, still there are two challenges in applying machine learning techniques in transportation. Increases in the rate real time data and the size of geographic regions we would like to consider simultaneously requires distributed algorithms to parallelize computations. Network Lasso for graph clustering provides a way of identifying unknown features for each of the transportation problems which cannot be collected easily. In such scenarios, we need a hierarchical model capable of identifying such unknown parameters.

Student's Involvement and Expected Outcomes:
Research Tasks
1.Comprehensive Literature Review on Machine Learning and Safety (mostly completed already)
2. Mobile Phone App Development (prototype has been designed)
3.Online data collection tool development
4.Synthetic data development (for prototyping purposes)
5.Prototype model development
6.Proposal Development (relevant deadlines AARP, Fall, 2016, NSF, Fall, 2016, Google, Fall 2016)

Prerequisites: The SURF-IoT researcher will be helping us develop the mobile phone app that will be used for data collection, as well as the website that participants will use to add information to records. In addition to doing the coding work necessary to make this project work, he or she will learn about the algorithmic and public policy aspects of the project. We would welcome a student entering his or her second third or fourth year, provided that student has completed ICS 31,32 and 33 with good performance. We would prefer a student who is eager to learn simple app development.

 Project #5:  Marching Cubes Made Tangible
Faculty Mentor:  Professor Jesse C. JacksonStudio Art

Project Description:
Marching Cubes is an algorithm that constructs a continuous three-dimensional surface from a collection of points in space. First presented in 1986 and later refined for the purpose of generating high-resolution renderings of medical scan data, Marching Cubes and its derivatives have since become some of the most widely adopted algorithms ever created. This algorithm’s particular geometric signature is frequently present in screen-based representations of three-dimensional information; it is a language that defines our virtual environments.

Marching Cubes Made Tangible proposes an interactive installation comprised of plastic construction units that permit participants to, through playful interaction enabled by media technology, directly experience the algorithm, the virtual language it represents, and the cultural residue it leaves behind. This project is the culmination of a ten-year sequence of new media productions focused on deploying this language in the sculptural realm, by interpreting the algorithm as a tool for provocative form making at a variety of scales.

Marching Cubes Made Tangible provides a means by which a person can engage with an algorithm—computational instructions that are the backbone of the Internet of Things—in a tangible way. The tactile nature the construction units, enabled by the universally familiar and culturally primal act of play, will render the abstract idea of an algorithm accessible. This project provides a way in which one of the foundational computational procedures of our hyperconnected world can be touched and manipulated, generating dialogue about the ways in which information technologies create the building blocks of contemporary culture.

Student’s Involvement and Expected Outcomes:
Marching Cubes Made Tangible is a project of the Speculative Prototyping Lab in the Claire Trevor School of the Arts. The student will be responsible for extending the success of a previous SPL project, Making Plastic Printing Sustainable, in which a research team of five students designed a closed loop polymer upcycling workflow for a fused-deposition additive layer manufacturing machine. The student will test and refine this workflow in the process of producing Marching Cubes Made Tangible prototypes. These prototypes will inform an exhibition of this body of work taking place in the Experimental Media Performance Lab in October 2016. The student will develop substantial skills in: computer-aided modeling; file preparation for computer-aided manufacturing; additive manufacturing machine setup, calibration, and repair; waste material preparation; and filament extrusion from waste and virgin material.

Prerequisites: The student should already be familiar with the operation of fused-deposition additive layer manufacturing machines. Beyond this, the ideal student would combine specific technical expertise—in mechanical and industrial engineering, computer-aided design and manufacturing, and user experience design—with a general inclination towards creativity and invention. Juniors who would be interesting in ongoing research with the Speculative Prototyping Lab during the 2016-2017 academic year are particularly encouraged to apply.

Recommended Web sites and publications: 
   Jackson, Jesse Colin and Luke Stern. “A Physical Instantiation of the Marching Cubes Algorithm.” In Synthetic Digital Ecologies: Proceedings of the 32nd Annual Conference of the Association for Computer Aided Design in Architecture, San Francisco, October 18-21, 2012, 239-247.:
   Lorensen, William, and Harvey Cline. "Marching cubes: A high resolution 3D surface construction algorithm." ACM SIGGRAPH Computer Graphics 21, no. 4 (1987): 163-169.:
   Rokeby, David. "Transforming Mirrors: Subjectivity and Control in Interactive Media." Critical Issues in Electronic Media. Ed. Simon Penny. Albany: State U of New York, 1995.:
   Specialists in Plastic Additive Manufacturing Website:

 Project #6:  MediCom – Integrating Multimodal Mobile Health Monitoring Data to Improve Doctor-Patient Communication about Medication Adherence
Faculty Mentor:  Professor John BillimekMedicine

Additional Mentors: Sergio Gago, PhD - Calit2

Project Description:
US has the highest health care cost inflation among leading developed nations.1 Between 2006 and 2010, the healthcare costs in US increased by a staggering 19%.2 Even more importantly, the overspending in healthcare in USA due to overutilization is estimated to be $750 billion. 3 It is deeply perplexing to see such statistics for a nation whose talented healthcare providers and technology are among the world’s best. One of the most promising solutions is patient-centered healthcare. But for that to succeed, patient has to play the most critical role, by taking ownership of one’s health, which would include educating oneself about one’s medical conditions, proactively following prescribed medication, continuously monitoring health metrics, regular wellness activities, and more. Patients are eager to play that role, after all it’s all about their health; however, the biggest impediment is the lack of data as well as technology to make that data highly intuitive and actionable.

Internet of Things (IoT) provides a great opportunity to fix this problem through interconnected devices, continuous data collection and reporting, which can enable seamless automated health insights delivered anytime, anywhere, on any device.

In the last few years we have seen a proliferation of portable health sensors, many of which are already available in market at affordable prices. However, the true value of the data collected from such sensors lies in integrating the data from all sensors, combining it with patient’s medical history, providing doctors the ability to monitor the changes in patient’s health metrics with regards to on-going medication, and making a patient more aware of the impact of his/her casual decisions pertaining to healthcare (such as not adhering to the timely consumption of prescribed medicines).

MediCom solves this problem through using the Internet of Things (IoT) technology based devices, along with human-computer interaction and informatics to deliver a simple, customizable dashboard providing comprehensive view of user’s health aspects. MediCom not just informs its users, but also educates them and assists them in carefully following their medication as well as pursuing wellness goals. A simple, yet powerful design will enable users to manage their health through MediCom, without getting lost in the details or complexity of the medical terminology. Besides individual health, social well-being is also promoted by MediCom through features such as Wellness Challenger and Voice of Patient which enable social interaction, while maintaining privacy when required. The following picture depicts a primitive design which we are currently working towards:

MediCom will be developed entirely based on Open Source software and utilities, in order to encourage collaboration from other universities as well as to offer this service to end users for free (by avoiding any licensing or subscription costs).

Student’s Involvement and Expected Outcomes:
Student Activities
•Write code snippets to collect and integrate the data from different health sensor devices (IoT enabled). This will include some preprocessing and transformations such as data normalization, using standard metrics, etc.
•Design and build a multi-platform seamless experience for users, through which users can access MediCom seamlessly over computer, tablets and smartphones. (This will be done in phases. Initially the focus would be to deliver a minimum viable product for the web interface only i.e. computer access)
•Perform comprehensive usability assessment of the interface's features through focus groups and rigorous A/B testing (the scope for this activity will depend on how much time is left after the above two tasks)
•Design creative elements for the interface to enable the delivery of integrated healthcare information from IoT devices in an intuitive and engaging way.

Expected Outcomes
•Data collection and reporting from multiple IoT health sensor devices
•An intuitive, actionable interface for providers as well as patients based on health metrics monitoring data
•Innovative features that will engage users towards greater health awareness leading to self-healthcare and patient-centric healthcare system

Specific Skills that Students will Develop
•Hands-on technical IoT experience (across a variety of popular devices)
•Basic data engineering (data collection, data transformation, data integration, etc.)
•Wed design and development
•Basic understanding of healthcare
•Applying technological innovation to meet patients' needs

Prerequisites: We are ideally looking for Computer Science or Informatics students with a good experience of web development and programming. The student must have taken courses and/or developed projects that involved building websites and solving problems through programming. The most important capability we are seeking is for the candidate to be a fast learner, as this project might require one to quickly learn new programming languages and start using them for development.

Healthcare experience or background is preferred, however, it is not mandatory at all.

Recommended Web sites and publications: 
   Jara, Antonio J., Miguel A. Zamora, and Antonio F. Skarmeta. "An internet of things---based personal device for diabetes therapy management in ambient assisted living (AAL)." Personal and Ubiquitous Computing 15.4 (2011): 431-440.

Pang, Zhibo, et al. "Design of a terminal solution for integration of in-home health care devices and services towards the Internet-of-Things." Enterprise Information Systems 9.1 (2015): 86-116.

Li, Xu, et al. "Smart community: an internet of things application."Communications Magazine, IEEE 49.11 (2011): 68-75.

Rohokale, Vandana Milind, Neeli Rashmi Prasad, and Ramjee Prasad. "A cooperative Internet of Things (IoT) for rural healthcare monitoring and control."Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), 2011 2nd International Conference on. IEEE, 2011.

Pae, YoungWoo, et al. "Using Mashup Technology to Integrate Medical Data for Patient Centric Healthcare." Future Information Technology. Springer Berlin Heidelberg, 2014. 71-76.

Viswanathan, Hariharasudhan, Baozhi Chen, and Dario Pompili. "Research challenges in computation, communication, and context awareness for ubiquitous healthcare." Communications Magazine, IEEE 50.5 (2012): 92-99.

Murphy, Judy. "Patient as center of the health care universe: A closer look at patient-centered care." Nursing Economics 29.1 (2011): 35-37.

Buchanan, William J., et al. "Patient centric health care: an integrated and secure, cloud-based, e-Health platform." (2012).

Maizes, Victoria, David Rakel, and Catherine Niemiec. "Integrative medicine and patient-centered care." Explore: The Journal of Science and Healing 5.5 (2009): 277-289.

Demiris, George, et al. "Patient-centered applications: use of information technology to promote disease management and wellness. A white paper by the AMIA knowledge in motion working group." Journal of the American Medical Informatics Association 15.1 (2008): 8-13.

Chawla, Nitesh V., and Darcy A. Davis. "Bringing big data to personalized healthcare: a patient-centered framework." Journal of general internal medicine28.3 (2013): 660-665.

 Project #7:  Mining Instagram/Twitter for Plant Data
Faculty Mentor:  Professor Bill TomlinsonInformatics

Description:  Project Description:
California has thousand of plant species, many found nowhere else on earth, which have evolved with and in response to its unique climates, soils, and fauna. Most of the settlers who came to California found a landscape and climate quite different from the well-watered places they had left behind, and this remains true to the ongoing growing population. Natives offer a palette as diverse and varied as the people who have made California their home. California’s indigenous peoples have an intimate knowledge of native plants through the daily utilization for every purpose imaginable, including food medicine, shelter, fuel, fiber, dye, and ceremony. Unfortunately, most immigrants to California have not historically valued this knowledge and much of it has been lost.

This project seeks to support California native plant horticulture by capturing plant life cycles, locations, and plant community diversity and distributing ethnobotanical information. Amateur and professional native horticulturalists in California will be able to capture plant images and geographic data using their mobile devices and add this data to a growing database of agricultural plants suitable for Southern California. This data will help others understand the environmental conditions conducive to growing a particular plant, including other plants it should be partnered with.

The core IT component of this project will involve using the Instagram/Twitter APIs to obtain relevant plant data (i.e., photo data, location of plant, date and time stamp, part of plant, plant health, etc.). This data will eventually need to feed into an existing database project. The database is built using the Django framework and is in PostGres.

Student Involvement and expected Outcomes:
The primary research activities the student would engage in would be:
1. Research what kind of data is commonly attached [scientific name, plant health, location etc] when a user uploads images of plants to either Instagram or Twitter. Determine which of the two platforms is most useful for this project.

2. Develop algorithms to mine such data from Instagram/Twitter so that it may be used in a third-party web application or to populate a third-party database such as the Southern California Sustainable Agriculture Plant Database built with Django framework (Python/Postgres).

Skills developed would include:
Programming experience, web application development, experience with data mining, and learning about the Instragram/Twitter API.

The primary research question the student would be involved with is:
Is it possible to obtain useful plant information (Images, Scientific Names, Other information) through mining tagged data from Instagram and/or Twitter?

•Interest in development of web applications
•Familiar with at least some of the following: Python, Java, SQL, PHP, Javascript
•Familiar with MVC frameworks such as Django, Rails etc.
•Experience with using APIs

Recommended Web sites and publications: 
   Instagram API:
   Twitter API:
   Crowdsourcing and Sustainability:
   Sustainable Agriculture:

 Project #8:  Proabot Flotilla - Flocking Autonomous Sailcraft for Oceanographic Research
Faculty Mentor:  Professor Simon PennyStudio Art

Description:  Project Description:
Proabot Flotilla is a collection of autonomous, solar/wind powered marine exploration and experimentation vessels, linked to internet via satellite. A flotilla of craft will conduct research surveys collecting oceanographic data. The flotilla will permit, for instance, multiple parallel paths of say 10 craft a mile apart, over extended distances, providing collection of data (water chemistry, currents, temperature etc) in a way that is impossible or prohibitively expensive for manned craft. Proabot Flotilla group will seek cooperation and collaboration with the UCI Oceans initiative, UCI Sustainability initiative, the Beall Center for Art and Technology, the UCI Newkirk Center for Science and Society, The Back Bay Science Center, the Newport Aquatic Center, and local Citizen Science initiatives. Realted project include Saildrone, Protei/Scoutbots, Seaglider (see recommended readings, below).

Proabot Flotilla research program leverages existing work by the MDP Orthogonal group on a radio controlled 8ft sailcraft of experimental design. Development of the project will occur in the following stages:

1. Radio control of sails and rudders with onboard realtime sensor feedback via onboard microcontroller and custom control unit. 100 m range, sea testing on Newport harbor/ backbay.

2. Installation and monitoring of basic sensor suite, including water temperature, craft speed, windspeed and direction, position via GPS and digital compass.

3. Marinised webcam direct to internet (Proabot website) with camera control via web.

4. Development of onboard semi-autonomous control

5. Satellite communication of sensor/camera data to web

6. Migration of mission planning and control to web.

7. Addition of custom mission specific sensors.

Student’s Involvement and Expected Outcomes:
All students will be involved in team based, radically interdisciplinary real-world design, construction and testing. This will include:
Aero- and hydro-dynamics, Mechanical, electromechancial and electronic design and fabrication, Precision machining, welding, metalwork, Microcontroller programming, especially with sensor and motor interfaces, Radio frequency, satellite and internet communications, Specialized internet/web programming and design, Boatbuilding, sailmaking and rigging,
Development of hybrid materials based structural and environmental solutions.

Prerequisites: The most desirable applicants will demonstrate:
Practical construction/fabrication experience
Sailing experience
Interest and past experience in environmentally activist projects
Interest and past experience in technical research and development
Proven expertise in more than one of the areas listed in ‘C’
A willingness to work hard and get dirty.

Recommended Web sites and publications: 
   TEDxOrlando - Cesar Harada - Protei:
   Cesar Harada: A novel idea for cleaning up oil spills:
   Autonomous Underwater Vehicles:
   Autonomous Underwater Vehicle ABE:

 Project #9:  TurtleBot with Qualcomm Snapdragon ARM CPU
Faculty Mentor:  Professor Solmaz S. KiaMechanical & Aerospace Engineering

Joint Faculty Mentor: Eli Bozorgzadeh

Project Description:
The objective of this project is to modify a robot platform called TurtleBot so that it can be controlled and operated by a microprocessor instead of its current arrangement, which works on a small laptop. The TurtleBot consists of a mobile base, 3D Sensor, laptop computer, and the TurtleBot mounting hardware kit. This robot runs on Robot Operating System (ROS). Robot Operating System (ROS) is a collection of software frameworks for robot software development, providing operating system-­‐like functionality on a heterogeneous computer cluster. ROS provides standard operating system services such as hardware abstraction, low-­‐level device control, implementation of commonly used functionality, message-­‐passing between processes, and package management. This project contributes to development of a robotic testbed for robust and energy aware distributed cooperative localization algorithms for mobile robots.

This is a joint project proposed by Professor Eli Bozorgzadeh from the Computer Science Department and Professor Solmaz Kia from the Mechanical and Aerospace Engineering Department. Professor Bozorgzadeh will provide the Snapdragon board and the required support for embedded system side of this project. Professor Kia will provide the TurtleBot robot and the support to learn and start with ROS programing.

Student’s Involvement and Expected Outcomes:
This is a supervised independent research. The student will work on adding ROS functionality to a Qualcomm Snapdragon microprocessor. Then he/she needs to use this microprocessor to replace the netbook controlling unit of a TurtleBot robot in Prof. Kia’s lab. The final deliverable by the student will be a TurtleBot functioning via Qualcomm Snapdragon board.

Prerequisites: This project requires strong background and knowledge about C++ and/or Python programing languages. Also, the student needs to know Ubuntu or Linux operating system. Familiarity with ROS is desirable.

Recommended Web sites and publications: 
   SS Kia, S Rounds, S Martinez, “Cooperative Localization for Mobile Agents: A Recursive Decentralized Algorithm Based on Kalman-­‐Filter Decoupling”, IEEE Control Systems 36 (2), 86-­‐101.
   ROS tutorial:
   Meet the Snapdragon Rover and the Snapdragon Micro Rover:­‐snapdragon-­‐rover-­‐and-­‐snapdragon-­‐micro-­‐rover