AoT Update - Community Partnerships

AoT Update - Community Partnerships

There were many motivations for Chicago’s Array of Things (AoT) project. While it is primarily an experimental research platform to measure the city and provide researchers with a testbed for new “smart city” concepts, AoT also aspires to be a research platform for Chicago educators, students, and residents.

In April, we concluded the second iteration of Lane of Things, an 8-week high school curriculum sponsored by the Motorola Solutions Foundation and developed by a team that included Kate Kusiak Galvin (UrbanCCD), Jeff Solin and Dan Law from Lane Technical High School’s Computer Science Department, and Douglas Pancoast, Satya Mark Basu, and Robb Drinkwater from the School of the Art Institute of Chicago.

As was the case last year, over 150 students worked in teams of three to learn about science, measurement, design and problem solving, data analytics, teamwork, and in the process, acquire hands-on experience with the concept of “Internet of Things” (or “IoT”)—an underlying enabler of the Array of Things.

For this second year of the program, IoT device platform makers Particle joined the team, providing the students with programmable, wireless networked microprocessors that served as the internal brains for their sensor “motes.” Students programmed these devices—called Photons—using Particle’s web portal. They learned how to make different internet services interact; for instance, programming the Photons to send data to online spreadsheets, streamlining the process of collecting and analyzing data.

Over the course of eight weeks, the student teams learned important skills, such as:

1.     Formulating an hypothesis or question to be answered through experimentation.  Although the curriculum revolves around sensors and IoT technologies, these are means rather than ends. To conduct a real scientific project, student teams first conceived of an hypothesis or a question. A good example is the project from Group 403. These students were interested in learning whether there is “a correlation between temperature, humidity, carbon monoxide, hydrogen, and UV levels in a greenhouse. The greenhouse gets the most sunlight out of any room in Lane Tech, so we wondered if there was any correlation with UV from the sun and the various gas levels in the room.”

2.     Developing an experiment.  Here the students designed a device that would take measurements relevant to their hypothesis or question. Group 708 designed a device that would let them measure “whether or not the time of day influences the amount of people that enter/exit the attendance office.” Typically, such an experiment would involve an observer with a clipboard, but the students used a motion sensor, placed in the doorway to the attendance office.

3.     System design and problem solving.  Once student groups decided on what kind of measurement to do, and what kind of sensor would be needed, they learned how to build the electronics that would use the sensor to gather data, as well as an enclosure and mounting system to position their devices for optimal measurement. Group 678 needed to enclose and mount their device in the dance studio in order “to record the level of sound in terms of volume and how loud a room gets, the temperature and humidity, and [use] a motion sensor to get an estimate of how many people walk by, get close, or interact with the photon. The three can all show correlation to how active the classroom is.”

4.   Data analytics and web applications. While taking measurements for two weeks, project teams stored their data in online databases and spreadsheets, allowing them to graph and analyze the data. To do this, students learned how to expose variables to Particle’s cloud, then program online databases and spreadsheets to pull that data. Group 709 built a system to measure water temperature and clarity in Lane Tech’s aquaponics laboratory in order to provide “early warning” of system failure. They used graphs to analyze the data and concluded that their “data did not reveal any tampering or major failures in the aquaponic system (which is good) and we are confident that the mote would have detected a major problem if it had occurred. We are considering leaving the mote up over the summer when power to the aquaponic system is most likely to be accidentally shut off.”

5.   Teamwork. Unexpected challenges often bring out the best in teams. Group 402 discovered a hardware issue that delayed their installation, and had to pull together under a deadline to resolve it. They describe it quite well: “The day before we were supposed to deploy, we came into class and found that the pins connecting the wires on our sound sensor were broken off. So, we spent the whole period re-soldering the sensor and wiring it to the breadboard. We missed at least 3-4 days of data pulling, but it all worked out in the end.”

What’s Next for Lane of Things?

The LoT team is already working on packaging the curriculum and developing a workshop to enable faculty from other high schools to bring the program to their schools.  And of course, the team is eagerly preparing for next year’s program, which will include teaching the students how to use the Array of Things application programming interfaces to incorporate data from the Array of Things! If you are a teacher or school representative interested in participating in future versions of Lane of Things, please contact us at urbanccd.education@uchicago.edu.

- Charlie Catlett, Director, Urban Center for Computation and Data

About UrbanCCD

About UrbanCCD

By the year 2030, the World Health Organization estimates that six out of every ten people on Earth will live in cities. In developing countries, such as China and India, booming populations and economic shifts will soon require the construction of massive new urban areas -- the equivalent of 20 New York Cities in China alone. In order to avoid the slums, pollution, and unhealthy conditions of many cities today, new design and management strategies must be developed to prepare for this urgent growth.
Fortunately, we are also at the dawn of a new era for urban research, fed by rapidly expanding amounts of city data. Research centers such as our Urban Center for Computation and Data at the Computation Institute -- a joint initiative of the University of Chicago and Argonne National Laboratory -- are at the frontier of using this valuable information to create new approaches for understanding and improving cities.
Existing cities also need to collect more data about themselves, and do more with that information to improve the lives of their residents. Sensor networks, such as the UrbanCCD’s Array of Things in Chicago, will be able to collect measurements on the environment, infrastructure, and traffic in higher time and space resolution than ever before, offering a “fitness tracker” for urban life. This more detailed data can help governments better allocate resources to areas in need, including using predictive analytics to address problems before they occur.
Open release of this data to the public will empower citizens to develop their own solutions and applications that improve city life. Our Plenar.io platform makes the data released by cities, federal agencies, and other sources more accessible than ever, allowing users to simply find all data available for the area of their choice without wading through complex and disparate spreadsheets. Custom dashboards built upon this platform will enable local governments and citizen groups to access and work with large, continually refreshed data without heavy investment in IT resources and personnel.
Urban designers and architects now need powerful computational tools that they can use to plan new developments on the scale of neighborhoods or entire cities. Advanced computer models -- such as our LakeSim platform -- can simulate the long-term interplay of energy, transportation, wastewater, and other infrastructure systems, along with social and economic processes, allowing designers to examine different scenarios with a single click. These capabilities will drive the design of more energy-efficient and livable cities that are resilient to climate change and other perturbations.
To make these visions reality, partnership is essential. Social scientists must work with computer scientists, academics must work with governments, and governments must work with their residents to insure that the cities of the future realize this new potential. The Urban Sciences Research Coordination Network, overseen by UrbanCCD, brings these groups together to forge unique collaborations, from agent-based modeling of urban health care interventions to projects on education, energy, and community vitality.
All of these efforts provide promising new approaches to understanding, designing, and improving the world’s cities. Computation and data are not just valuable resources, but a common language that can unite research disciplines, public institutions, and residents in efforts to make our rapidly urbanizing world more livable, healthy, and efficient.

- Charlie Catlett, Director, Urban Center for Computation and Data