It’s 5:30 a.m. The start of Ms. Smith’s day. Instead of a loud alarm, a device next to her bed pulses lights on and off, and a gentle voice tells Ms. Smith to wake up. Gradually, she stirs. The voice belongs to an IoT device, connected to the internet and running a “wake up” program that she configured.
She asks, “What are my plans for today?” and it recites her scheduled meetings and activities. She showers, dresses and heads out the door. The IoT thermostat senses that she’s left the house and lowers the temperature.
She drives to work in fairly heavy traffic. Cameras equipped with computer vision are mounted on streetlights at each corner, and many are also mounted mid-block. The cameras are smart, equipped with Intel Movidius vision processors that monitor the traffic, counting cars and communicating with other cameras and into the cloud. Some of the smart devices also have temperature and humidity sensors, and a few have GPS (for accurate location reporting) and microphones to capture the sound of braking and collisions.
These cameras monitor the number of cars traveling and compute the speed of traffic. Instead of sending video images, however, this smart camera is sending aggregate numbers of cars at defined intervals. This information is received by a small data center located near the cameras—more specifically, an edge data center, charged with not only processing the data that comes from the thousands of cameras and sensors located nearby, but also with controlling the traffic signals to maximize the flow of traffic.
Ms. Smith’s ride through the long stream of traffic is slow, but steady. Although her car’s speed is lower than she prefers, at least she rarely stops for traffic lights. The computer vision sensors and processing of the data at the edge data center make this possible. Ms. Smith doesn’t realize how much data is moving around her—and she doesn’t really care, as long as she gets to work on time.
Once at her job, Ms. Smith begins to monitor the manufacturing, inspection and packaging of auto parts. She sits at a computer terminal, overlooking a window that shows the production floor. She monitors a robot that performs complex mechanical tasks. This robot—an Industrial IoT (IIoT) device controlled through the internet—has moving “fingers” that perform intricate assembly tasks as well as “arms” that perform less “skilled” tasks. A dozen cameras mounted on the robot monitor each minor movement, and another camera, also an IIoT device, is trained to recognize the normal production flow. If something isn’t right, Ms. Smith is alerted. This rarely happens at the beginning stages of manufacturing—systems are finely tuned, fully tested, and the IIoT devices powering the manufacturing rarely fail.
After multiple stages of assembly, the product nears completion. Computer vision that is built into the assembly and manufacturing devices monitors the product at every step of the process. A bank of cameras inspects the completed product from multiple angles as it progresses down a conveyor toward the packaging area. If any defects are detected, the item is removed from the belt.
Ms. Smith’s responsibility is to monitor the IIoT equipment, taking appropriate measures if defects are located or if an excessive number of defects are reported, and intervening if something goes wrong.
At lunch time, she goes to the company cafeteria. Rather than wait in a long line, she grabs some quick food from a refrigerator and gets a soft drink. Her purchase is automatically rung up—as she walks past the register, the RFID tags on the items she has selected are scanned by an RFID reader and an RFID tag on her employee ID card shows she’s buying the items. She will get a statement sent to her company email account, showing what she just purchased.
As scheduled meetings or appointments approach during the day, she’s reminded of them, at a preset time before her meeting, with a message on her computer screen and a tone in her speakers. The schedule has automatically been shared across the company computer, her phone and any device that uses the same calendaring application.
At the end of the day, she reviews reports generated by the IIoT equipment that was involved in the day’s processes. This data—the number of products manufactured, the number of defects found, the types of defects, the performance of each robot and other details—has been generated for each device manufactured, and a tag with a unique number has been attached to each.
The aggregated data is approved and sent on to the corporate data center, where it will be reviewed. More complex analysis of Ms. Smith’s production line, in addition to those of many other production supervisors, will be analyzed by the corporate systems. Inventories will be reconciled, supplies will be ordered, and, by morning, everything will be ready to go again.
Ms. Smith walks out of the building. An RFID reader at the door scans her badge as she walks past it. Computer vision sees her approaching the exit and walking into the parking lot. The drive home is much like her drive to work. Computer vision devices on the road monitor and control traffic signals. Her ride home is slow—but again, she misses most of the red lights.
Fifteen minutes before she gets home, the thermostat automatically turns on the heat (or cooling) so that the temperature is comfortable when she comes in the door. Finally at home, she walks inside, and the lights turn on. To relax, she turns on the TV, and the lights in the room automatically dim, making it easier for her to watch her favorite show. As she’s ready for bed, she says, “Turn down the lights,” to her digital assistant. “Oh, and wake me up at 5:30,” she says. “No, make it 6.” Lights in the other parts of her house dim, the lights in her bedroom slowly fade, and so does Ms. Smith.
In the course of a single day, the IoT and IIoT have woken her up, saved energy, eased her ride to and from work, enabled her to do her job way more efficiently and productively than would be possible otherwise, let her buy lunch quickly and painlessly, managed her workday schedule—and turned off the lights. This is just a small sample of how the IoT and IIoT will enhance our lives.
How is the IoT triggering business growth and transportation? See new research from Forbes Insights in partnership with Intel
