August 17, 2016 Leave a comment
Imagine the Internet of Things–empowered experience of new students arriving at a college campus for the first time. They’ve downloaded the school’s app, which directs them to open parking spots that are student-eligible and close to their dorm rooms. It also prompts them to enter their license plate numbers and registers their cars. They’re directed to their dorms, and notifications update the resident advisors’ dashboards and brings up their names on a welcome screen in the dorm’s entry hall. The app leads each student to their rooms, where their phone opens the door to reveal a room with a tablet pre-loaded with materials specific to their classes as well as the non-digital materials for the classes they will be taking already piled on the bed. The app shows their class schedules, class locations, and assignments. It lets them browse and sign up for extracurricular activities and shows open seats in computer labs, group study rooms, and the library. A phone bump pays café bills and laundry machines. Meanwhile, intelligent security cameras watch over public spaces and identify visitors whose faces the software does not recognize and alert campus safety personnel.
On this modern campus data is integrated, and automation provides a student experience that is safe, personalized, and always connected. This data is correlated with student performance data to give the school insight into specific student engagement patterns to ensure that every student needing assistance receives it before issues become acute. Just as baseball managers have adopted “pitch counts” and use advanced analytics (sabermetrics) to direct action before negative events occur, higher education institutions use data to direct actions and interventions that drive better outcomes for students and
the institution. Data from parking systems, campus access cards, wireless access points, and cloud productivity tools are combined to paint a previously unavailable picture of student engagement. Is there correlation between engagement and the number of weekends spent off campus? How does use of school resources such as group study spaces or the library correlate with grades? Does it differ by major? Cloud-enabled machine-learning models applied to student engagement and performance data can help institutions materially increase graduation rates, just as schools such as the Tacoma and Cleveland Metro school districts have done.
The Internet of Things Is Exploding
Few of us had heard of the Internet of Things only a few years back. Big data was the hot topic, with promises of new insight from advanced analytics. If big data is the heart of advanced analytics, IoT is the pumping blood. Today IoT combines with cloud-enabled analytics to bring gains in efficiency and cost savings while at the same time making a reality of services that were previously impossible or cost-prohibitive.Gartner predicts IoT will explode: connected endpoint devices are expected to grow 32 percent year over year through 2020, reaching an installed base of 20 billion devices. In 2020 alone 6.6 billion “things” are expected to ship, and hardware spending on connected endpoints will reach $3 trillion.
Educational institutions have begun to recognize the potential benefits from these IoT solutions applied to their campuses. Operational efficiencies can lower costs, and reduced consumption can lower carbon footprint, aligning with an institution’s goals for fiduciary and social responsibility. Cloud service data centers are in some cases carbon-neutral, reducing the school’s carbon footprint rather than just shifting it to a cloud provider. These same technologies also generate data that can be used to personalize campus experiences.
Why the sudden explosion? Wireless and Wi-Fi networks are ubiquitous, as are the devices that use them to communicate. The phones in our pockets are relatively expensive examples, powerful and chock-full of sensors (temperature, compass, acceleration, energy use, sound, light, radio waves, and more). But the cost of the simplest of sensors and the Wi-Fi chip needed to connect them has fallen to a few dollars and continues to decline. Cloud computing provides the centralized collection, storage, and analytics systems and algorithms necessary to make sense of the resulting masses of data.
The history of building management systems and the energy efficiency they now yield provides an example of the concrete benefits of cloud-enabled IoT in higher education. Twenty-five years ago buildings were completely dumb — they did not collect information about how they were operating, much less communicate it. The subsequent inclusion of building automation systems allowed a facilities manager to see a building’s current status, but the data stayed local and did not include history. More recently data was collected over time across multiple buildings, but only if they shared systems of the same generation from the same vendor. Only in the past few years has building data been normalized across multiple building automation systems and equipment vendors, stored so that patterns over time become visible, and compared with other customers’ data collected from hundreds of other buildings. Today you have systems that let you see in real time how your energy is being consumed across all of your buildings, see current status and detect faults in your equipment, and identify patterns in historical equipment telemetry in order to predict and prevent failures before they happen. All of that leads to reduced energy usage (10–20 percent, increasing with time and additional analysis) and facilities tickets that are declining and focused on prevention and the highest priority failures. Both save you money. At Microsoft we’ve implemented such a system and are on track to cut costs by 18 percent of our previous expenditures on energy — and that’s on top of the earlier gains made by ensuring unused equipment is turned off at night and replacing energy-inefficient lights. Schools including Carnegie Mellon University and the Peirce School in Massachusetts already benefit from these systems.
Industry adoption creates a huge IoT and cloud computing employment opportunity. A university’s own IoT projects, such as building and energy management, can serve as a live lab for learning, enabling students to add value to real-world solutions. At the same time, students learn valuable cloud computing and analytics skills necessary for tomorrow’s jobs. This data can also be rich fodder for faculty research projects, presenting an opportunity to collaborate across schools and combine data sets to increase the accuracy of data models.
How can a school begin to leverage cloud-enabled IoT? Start with existing data — many on-campus systems already generate data that can be combined and analyzed to generate new insight. Identify a cost-saving pilot as a first step; energy efficiency would be an excellent and timely choice for any school not already running a second-generation system. Iterate (as with any tech). As confidence grows and savings are realized, invest in additional services that will allow your school to stand out from your competitors and attract great students. Then go big by adding new sensors, combining new and existing data sets from different systems, and creating new applications. Leverage the cloud, which provides centralized data collection and analysis, built-in scalability, preconfigured environments optimized for the IoT, and powerful machine-learning algorithms. Then bask in the admiration of your peer institutions!
Seth Atkinson is senior business development manager for Worldwide Education, Microsoft. Rob Curtin is director of Higher Education for Worldwide Education, Microsoft.
© 2016 Seth Atkinson and Rob Curtin. This EDUCAUSE Review article is licensed under Creative Commons BY 4.0 International.