Smart Driving Resulting from IoT and Big Data Telemetics
The Internet of Things (IoT) is part of any conversation about where smart technology is heading. People in IT are expecting amazing new ideas to come out of a world where everything is connected, providing a tremendous amount of data to guide decisions made by people. The impact on our daily lives is going to be real. We are already seeing the beginning of this revolution with smart refrigerators, smart watches and generally smart buttons on everyday products and appliances.
We haven’t witnessed an affordable smart car. Yet! Google is leading the way with its self-driving cars involved in road tests in California (one self-driving car had an accident this past summer and obviously it was the fault of humans).
Established manufacturers have been toeing the smart technology conservatively. For instance, Bluetooth technology was invented 15 years ago, but in 2015 it is rarely a standard. Challenges from new competitors Google and Tesla have jumpstarted the big auto manufacturers out of their inertia. Volvo recently unveiled new technology that allows its car owners to provide access codes to other for one time access to their car trunks. Ford unveiled to huge success its self-parking technology in cars and now some vehicles come with navigation systems that can access real-time road conditions and other relevant information.
When a vehicle’s communication system is connected with a network and you combine that with information technology, you get the field of telematics, a critical component of the new smart cars about to roll off the assembly lines. Smart cars will have three main modules:
1. Collection of data from a variety of sources
2. Computing capabilities to analyze data and recognize patterns
3. Communication of results in actionable points to systems, vehicles and users
Data collection includes an expansive net of sources from vehicle parameters, such as speed, to road conditions gathered from sensors implanted on the road to weather conditions collected from online weather reports and forecasts. Smart location analysis, computing how all these elements are interacting with each other to create road and traffic conditions is a key concept of smart mobility in vehicles.
A vehicle’s sensors will pick up information about the immediate circumstances on the path of road it is traveling on, but cannot know what occurred on the street up ahead five minutes ago to predict what road conditions will be as the vehicle will reach that point of the street. This gap in data can be eliminated with telematics and smart mobility in conjunction with location analysis.
Before vs. After
There is no better way to explain this than an illustration of before vs. after of implementing new technologies:
In the past, a mother may be on her way to pick up her daughter after a soccer game, but encounters a foggy patch on the road. She slows down a little, but not sufficiently to avoid the car from spinning because the fog has crystallized into ice on the road due to the low temperature. As the car spins, it slides over some debris on the shoulder of the road that destroys a tire. The mother has to call a pickup truck to tow her car to the nearest garage where she waits almost two hours before her car is repaired (and pays a hefty bill before leaving).
Smart mobility can completely change this scenario in a multitude of methods, some of which we list below:
1. Road sensors pick up the ice forming on the road and transmit this data to online weather and road services that, in turn, send the information to vehicles driving in the area. The vehicle’s computer analyzes incoming data and creates a hazard alert, warning the driver to slow down because of treacherous icy conditions.
2. The sensors pick up data regarding debris on the road as cars drive over the debris and send this information to the local municipality’s road crews who dispatch a team to clear up the hazardous objects.
3. Weather services alert road and highway services about foggy and icy conditions that then display the message on electronic road signs to alert travelers of the danger.
4. Highway services, alerted to the icy conditions, send out a team to spread deicing material over the dangerous area.
5. The smart vehicle’s computer analyzes historical data along with current conditions to warn the driver of the risks of continuing with the journey.
6. Vehicle speed is automatically reduced when data is aggregated from all sources and the computer figures out that speed needs to be lowered for safe driving.
7. The vehicle’s computer offers alternatives to the driver: take a 30-minute detour, wait for 45 minutes at a local restaurant, or continue at a reduced maximum speed.
8. Once the drivers selects an option, the computer which was pre-planned to notify the daughter of any delays, sends a text message to the daughter as to when her mother is going to arrive, preventing calls and a distracted driver.
How Faraway is This Future?
The technology is already available and auto manufacturers will eventually start manufacturing vehicles with these high-end sensors. The next step, getting governments and cities to use plan future projects with smart mobility in mind will take some work, but there are economic incentives to do so. Economists have long touted the cost to the economy of a region due to high traffic congestion because of the valuable time lost by people stuck on jammed roads. Truckers know the feeling well and would love to have smart roads and computing powers which would help enhance their delivery times. Cities have started the process of upgrading their systems as some authorities provide multimodal data to commuters using public transport.
IoT will allow the aggregation of data from thousands of sensors and will enable detailed analysis that will provide specific alternatives to users. When all is said and done, it will mean safer roads and more convenient travelling which will boost local economies.