BARCELONA -- At Mobile World Congress, hundreds of companies showed off new smart city technologies, some that are just in the start-up phase while others are being implemented in select cities.
One concept further along in deployment is a smart parking meter made by Paris-based Parkeon that's in use in 12,000 locations, ranging from New York City to beaches in Australia. Parkeon showed a deluxe meter that takes credit cards and includes a display that can offer news. In Sydney, for instance, the parking meter provides tips on surfing conditions off the Australian coast.
During MWC, Parkeon and Sierra Wireless announced that Sierra Wireless AirPrime HL Series embedded modules will be used to enable cellular connections to the smart city parking meters, running on 2G, 3G and 4G technologies.
Parkeon also introduced a mobile parking service app called Whoosh! that drivers can use to pay for parking through phones, tablets and computers. Parkeon is the largest smart parking-meter provider globally.
The Parkeon-Sierra Wireless partnership is an example of how smart city technology is taking off, thanks to a growing number of low-cost modules and sensors that can be connected wirelessly to cloud-based services for payments and other intelligent services. When data collected by inexpensive sensors is collected and analyzed in a big data manner, it can be used to help orchestrate smart city initiatives.
Near the Parkeon demonstration, a startup called See.Sense from Northern Ireland demonstrated a $99 rear bicycle light with a number of smart features. In addition to connecting to a smartphone to alert a user to a theft of a bike, the ICON device includes an accelerometer that can be used to measure the impact from hitting a pothole or to record a crash. That data could be forwarded to government officials to alert emergency crews of a crash or to let a road crew know where to patch up the worst potholes, See.Sense officials said.
See.Sense was like a number of companies showing products at MWC that want to use data gathered by average citizens, in a crowd-sourcing manner, to connect to big data repositories where city problems can be analyzed to help predict future needs. One possible concept for the bike light is that it could someday include an air quality sensor that would give a view into pollution along crowded roadways, the company said.
A technology shown at MWC by Seattle-based Inrix relies on crowd-sourcing data from cars driven along highways. The company used a large monitor to show hundreds of cars moving along highways, supplanted by data from stationery sensors along the roadways.
When a car’s wipers are turned on, that data can be combined with data from nearby cars and with existing big data showing the contour of the roadway and average weather conditions. With an insight from car and stationary sensors that it is raining in real time, a big data repository would know precisely the history of freezing rain conditions along that portion of highway that could indicate whether salt trucks need to be sent automatically to the scene.
Traffic and driving intelligence data are already being collected in large cities, but the growing use of low-cost sensors and car-based computers will expand the number of insights that cities can glean to make automatic decisions, analysts said.
BlackBerry officials at MWC noted that such car-based data will help the development of entire networks that could help safely guide autonomous vehicles. Already, newer model cars may have up to 100 different computers, which are used to prevent auto accidents, such as collions, among other tasks.
In coming years, data from sensors in cars, embedded along highways and in traffic signals is expected to be shared with the wireless networks surrounding crowded streets so that cars react to the network — instead of each other — to come to a stop at an intersection or to avoid crossing a center line, said Derek Kuhn, senior vice president for the Internet of Things at Blackberry in a roundtable with reporters.
That level of driving intelligence is just one example of the complexity that smart cities of the future are bound to face.
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