Statistics say, "54 Million car units are sold every year in the world." That means 54 million cars are getting added to the existing cars every year.
Imagine if you go out on a Sunday, with your friends or family to your favorite diner for dinner and you cannot find a place to park your car. Wouldn't it be disappointing?
Well, the people of San Diego have nothing to panic about, as they have got their street lights to give them a helping hand.
The city of San Diego is all set to deploy world's largest City-based "Internet of Things" platform which will use street lights in this process. It is partnering with General Electric's (GE) to upgrade it's streetlights, keeping in mind provision of several facilities to it's residents.
“Fostering innovation and improving infrastructure are important to enhancing the lives of all San Diegans,” Mayor Faulconer said. “This new technology will give the City and developers the opportunity to make our neighborhoods safer and smarter.”
The city is replacing its 1400 streetlights with these "Smart Streetlights". Smart nodes will be installed in them that can use real-time anonymous data to do things like escorting the vehicles to the nearest parking spaces or to help first responders during emergencies.
Most of the times, accidents take place and there are not many evidences or eye-witnesses. People hesitate to call the police and some of them are inattentive. This might in turn succor the assailant to escape or the victim to succumb to the injuries. With the installation of this powerful technology, the rate of occurence of such incidents will be diminished considerably.
The deployment of 3,200 smart sensors will be the largest city-based deployment of an “Internet of Things” platform in the world. The streetlights will be equipped with smart sensors which will cover an oval-shaped area of about 36 to 54 meters. The first job of these sensor fitted lights would be to guide the drivers to empty parking spaces and for this motive, apps will be developed which could be employed by the user. It will also be able to potentially alert traffic enforcement officers regarding illegally parked cars.
Subsequently, these smart lights can be utilized in several other ways to create more services to the community.
For starters, the city “expects to learn what intersections are the most dangerous and need to be redesigned, based on information on near misses, not just the accident data. It's a whole new way to improve pedestrian safety,” said David Graham, San Diego's deputy chief operating officer.
He also believes that this technology can easily be hooked into city's already existing ShotSpotter network to automatically locate the source of gunfire. The sensors could be put into service for detecting other sounds too such as of a car crash or a broken glass and immediately alert the police or call for the ambulance. This could reduce the hard work involved in police-patrolling.
You might be wondering, this might possibly consume a lot of energy, right? But the city officials are convinced that this will reduce the energy costs by $2.4 million annually. This will result in reduction of energy costs by 60 percent. However, this will actually be made possible by the usage of sensors which will dim and brighten the intensity of light depending on the natural light conditions.
The Adaptive Control System is an advanced SDG&E approved “meter” that captures real time interval data, monitoring and notifications for maintenance purposes and also provides GPS coordinates at each fixture. Over the life of each fixture the system automatically ramps up power as needed to meet specified lighting standards.
The 3,200 sensor nodes across the city are the latest step in creating a smart network. There is the potential to expand to another 3,000 points in the future.
The anonymous information from the sensors can be used by developers to create apps and software that can benefit the community.
Installation of the new lights will begin citywide this summer and the project is expected to be completed by fall 2018.
5 Comments
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