Smart Parking Spaces  

I've long been enthusiastic about ways of monitoring our environment for useful purposes (as opposed to the vast amount of time and money spent creating over-the-top surveillance apparatus'). This article at Technology Review describes a new example of gathering data that can be useful in reducing energy use, even if it is just the small amount of fuel people wasting driving around in circles trying to find a parking spot - Find a Parking Space Online. One day, your GPS co-driver might start telling you where you can park as well as where to turn (and where to slow down).

This fall, San Francisco will implement the largest mesh network for monitoring parking to date. Around 6,000 wireless sensors from the San Francisco company Streetline will be fixed alongside as many parking spots, monitoring both parking availability and the volume and speed of passing traffic. The city hopes that displaying information from the sensors on Web maps, smart phones, and signs on the street will reduce the traffic and pollution caused by circling cars.

A mesh network differs from a typical wireless network in that there's no central transmitter: every node can transmit to every other node. Mesh networks have generally been used for environmental monitoring, or to grant wireless devices Internet access.

When sensor networks have been deployed roadside, it's usually been to monitor traffic, not parking. In urban areas, traffic-monitoring systems have been used for congestion pricing: during business hours in downtown London, for instance, the license plates of cars are photographed, and the drivers are sent a bill. Some parking garages also have signs that tell drivers where the available spaces are, but such systems generally rely on manual car counting, not sensors.

In San Francisco, however, clusters of plastic-encased, networked sensors are embedded in the surface of the street. The main sensor in the cluster, which is commonly used to detect cars, is a magnetic one, says Jim Reich, the vice president of engineering at Streetline. Magnetic sensors detect when a large metal object locally disrupts Earth's magnetic field. One challenge with magnetic sensors is avoiding false positives. "We rely on the magnetometer the most, but in order to fix errors, we use other types of sensors [that] give you much higher reliability," says Reich. He won't elaborate on the supporting sensors, but he says that the Streetline system has a high ninety percent accuracy in recognizing parked cars.

To relay information, the Streetline sensors use Dust Networks' SmartMesh system, a spinoff of the Smart Dust project at the University of California, Berkeley, funded by the U.S. Department of Defense. Dust Networks CEO Joy Weiss says that SmartMesh networks are more than 99.99 percent reliable. SmartMesh and Streetline's technology combined gives the nodes an average lifespan of 10 years on only two AA batteries. "We were really the first ones able to build an entire network where every node in the network is able to run on batteries for years, and at the same time deliver very high reliability," says Weiss. "In most [other networks], these are a trade-off."

Dust Networks uses several techniques to combine efficiency and reliability. The first is redundant routing: if a signal doesn't go through the first time, the sending node tries other nearby nodes, or tries the same node after a period of time. A technique called channel hopping circumvents interference by assuming that changing channels every few seconds is more efficient than trying to find a good or bad channel, says Weiss. To save power, she adds, the nodes go to sleep in between transmissions.