The Internet of Things (IoT) will eventually create an unimaginable avalanche of data (read Big Data) through millions of devices connected to the Internet. But what kind of data and who are the companies that are implementing both IoT and Big Data to get their work done?
The IoT will create streams of data
Speaking to Big Think, Christ Curran, the Chief Technologist of PwC, uses the example of a door in a warehouse to explain the streams of data that will result from devices connected to the Internet. Every time the door opens, a sensor records a door opening, a time of day, day of the week, maybe the temperature of the facility or how long the door was open. That door is creating streams of data, and it is the patterns in the data and the trends they might represent, that businesses can use.
Imagining the information gathered from just one door, the sheer volume of data generated by a business operation becomes too vast to make sense of. However, EMC and IDC point out in their latest Digital Universe report that not all data is useful. Organisations need to focus on high-value, ‘target-rich’ data that is (1) easy to access; (2) available in real time; (3) has a large footprint (affecting major parts of the organisation or its customer base); and/or (4) can effect meaningful change, given the appropriate analysis and follow-up action.
UPS, Big Data and IoT
United Parcel Service (UPS), one of the largest shipping companies in the world, is one example of a company that analyses the data from connected devices to gain insights and improve business.
UPS uses data created by 55,000 drivers, 100,000 vehicles and 8.8 million customers to reduce costs, improve efficiency and reduce the environmental impact of its business. UPS uses sensors on its delivery vehicles to monitor speed, miles per gallon, mileage, number of stops, idling time, and the condition of vehicles.
The company deployed project ORION (On-the-Road-Integrated Optimization and Navigation) in October 2013, which uses hundreds of millions of address data points, plus other data collected on the deliveries, to optimize delivery routes for efficiency. The project costs $ 1 billion a year and is projected to be operation on all North American routes by 2017.
With 250 million+ data points, ORION is capable of delivering tens of thousands route optimizations per minute based on real-time information. Optimized routes, reduces travel distance, time and fuel. A reduction of 1 mile per day for every driver can save the company as much as $50 million a year in fuel, vehicle maintenance, and time, Myron Gray, president of U.S. operations, told Bloomberg at the time of the ORION launch.
Disney World uses data gained from its MagicBand to run a smooth business and optimize customer experience. Disney World’s MagicBand, a waterproof plastic wristband that contains a radio that can transmit more than 40 feet in every direction, is a great example of IoT and big data working together to create a magical experience of surprises and satisfaction for visitors. Visitors can use The MagicBand to check into their hotel room, order food, book a table at a restaurant, go on rides and reserve a spot for special attractions. No more cards or money, just tap your MagicBand and you go through the turnstiles. Walking into the restaurant, You’re greeted by name and as you sit down, your food arrives, just as you pre-ordered it.
This convenience is thanks to the wristband and its sensors which transmit information about visitors’ movements, so the Park’s personnel know beforehand the instant you’ll arrive anywhere in the Park.
The MagicBands with their sensors, the thousands of sensors they talk with, and the 100 systems linked together to create MyMagicPlus create streaming real-time data about where visitor are, what they’re doing, and what they plan next. Invaluable information if you want to provide unforgettable customer experience.
UPS and Disney World are joined by many other companies who are using big data and loT to improve business operations and give us a glimpse of a future that might have less frustrations, primarily among them waiting – waiting for a delivery, waiting in line, waiting for a table.