Artificial Intelligence in Smart Cities - How Does It Make the City Smarter?

Smart cities are cities that use different types of electronic IoT to collect data and then use this data to manage assets and resources efficiently. Gurugram is a smart city situated in India; citizens who live in Gurugram don't need to rely on traditional forms of communication with their local utilities and service bodies. This has removed the pains of traveling to local governing departments and has completely eliminated the need for long queues and registration processes. The Gurugram Municipal Cooperation (GMC) uses artificial intelligent chatbots to help these processes along.

Here are a few ways we can use AI to make cities smarter:

1. Chatbots have proved to be very useful in navigating the government sector leading to simple and effective workflows. Every smart city is designed to solve a specific problem, and thus each smart city has different missions and objectives. In the context of India, a mission for developing and establishing 100 smart cities was launched to provide a sustainable environment and infrastructure for its residents. It's not physically possible for human agents to process a large volume of queries as well. There is clearly a disconnection between the populace and the local body in many towns and cities. In this case, automation can solve some of the common day-to-day hurdles.

Artificial intelligence can be used to understand the daily patterns of communication. Between phone calls and chat, there has been a trend for consumers and customers to prefer using chatbots. Even popular retail brands have started to use AI chatbots as part of their conversational marketing efforts to give their customers a personalized experience. This not only adds to customer retention but is more likely to convert an enquiry into a deal.

2. Adaptive Traffic Signals have been applied in cities such as Los Angeles, San Antonio and Pittsburgh. These technologies use real-time data to change the timers on traffic lights to adjust the flow of traffic. This has improved travel times for city residents by 10 per cent and in some areas with outdated traffic signals by 50 per cent. Better traffic flow not only makes driving safer and pleasant but also can have immense economic significance. The Texas Transportation Institute has estimated the cost of traffic congestion at USD 87.2 billion in wasted fuel and lost productivity.

City traffic can definitely affect how our lives improve. Better traffic flow and sensors could better public transportation such as taxis, Uber, Lyfts and buses. This would directly affect affordability for these app-based taxi services which tend to have surge pricing based on traffic conditions and taxi availability. The Massachusetts Bay Transportation Authority and others tap into real-time information to make accurate arrival-time predictions available to the public. This is a game changer and something only smart cities can pull off!

3. Surveillance and Security are going to play a major factor in smart cities in the future.GTS predicts there will be about 1 billion security cameras used around the world by 2020. While the placement of security cameras has sparked a debate about privacy and a militarized state, the presence of cameras has also made improvements in public safety, reduced crime rates, and catching terrorists. Unfortunately, the number of cameras will produce far more data than human operators will be able to manage. Machine learning and artificial intelligence will help improve facial recognition, tracking and other aspects of security detection.

Government agencies are now developing means to train AI systems to identify specific objects and activities in imagery. There is research being done for real-time monitoring of multiple videos feeds through a Deep Intermodal Video Analytics project, run by Intelligence Advanced Research Projects Activity. GTS is also developing a metropolis platform designed to use deep learning AI to help with analysis.

4. Water and Power are important resources to manage in a smart city. AI can be leveraged to streamline power and water usage. Google claims that AI has cut power requirements in its data centres by 40 per cent. Cities are now using smart grids to manage power better. Solar-powered microgrids can be used in airports as illustrated by the city of Chattanooga in Tennesee. AI is also being applied to water metering to curb excess water and find leaks.

5. Public Safety can be completely revolutionized if law enforcement agencies apply predictive modelling and AI framework to run checks against criminal databases. License plate reader technology can also be used by the police to find stolen cars and identify expired registrations. There are of course privacy concerns when predictive policing systems are used; no one wants a science fiction police state like the Steven Speilberg movie: Minority Report! There is a lot of work to be done before these technologies can be used effectively for the public.

There is immense potential for AI to change the lives of residents in smart cities. U.S. and China have already deployed most of these technologies in various states and cities. It will only be a matter of time before other countries adopt these technologies to better the life of their citizens.

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Broadly Useful Language Goes Past AI Deep Learning

A group of Massachusetts Institute of Technology analysts area unit serving to specialists advance in AI Deep Learning and creating it less complicated for novices to understand computerized reasoning. The analysts alluded to a completely unique probabilistic-programming framework named "Gen". They displayed it during a paper at the programing language style and Implementation meeting as these days. The scientists composed calculations and models from varied fields. PC vision, apply autonomy was a little of the  Artificial Intelligence Techniques that were utilized. They did not compose the superior code physically rather like work with conditions. better of all, info or universally helpful language provides them an opportunity to compose advanced models and deduction calculations.

For instance, the analysts exhibit that a brief info program will deduce the three-D body presents during this test. It is, in fact, a hard laptop vision deduction task that has applications in multiplied reality, freelance frameworks even as human-machine associations. This program incorporates components that perform AI Deep Learning, illustrations rendering and forms of chance reenactments off camera. the ultimate product is best exactness and speed owing to the consolidation of those totally different strategies.

As indicated by the analysts, info may be utilized effectively by anybody. It alright could also be utilized by tenderfoots to specialists because it is basic and currently and once more owing to the robotization. It has to be compelled to be less complicated for specialists to quickly emphasize and model their AI profound learning frameworks during this method increasing potency.

The analysts, in addition, approved info's capability to disentangle data examination by utilizing another Gen program. This program consequently makes refined factual models often utilized by specialists to assess, translate, and anticipate elementary examples within the data. It provides purchasers an opportunity to compose a handful of lines of code to reveal experiences into aviation, monetary fund patterns, the unfold of illness, casting ballot styles among totally different patterns.

The previous frameworks needed an excellent deal of hand cryptography for precise forecasts. this can be not similar to previous frameworks. Google discharged AN ASCII text file library of Application Programming Interfaces (APIs) that helps fledglings and authorities consequently produce AI frameworks while not doing a lot of science called TensorFlow. The stage is democratizing some components of AI profound learning. it's strained and high-ticket once contrasted with the additional intensive guarantee of AI as a rule because it is targeted around profound learning models.

Recreation motors, applied mathematics, and Probabilistic models area unit different AI Deep Learning Techniques accessible. The scientists required to consolidate the simplest of all universes into one. This incorporates robotization, ability, and speed. info is been utilized for AI profound learning analysis by outer purchasers. as an example, info would be utilized for three-D gift estimation from its profundity sense cameras utilized in mechanical autonomy and distended reality frameworks. Intel would do that within the organization with Massachusetts Institute of Technology. it's in addition change of integrity forces on applications for info in physics mechanical technology for collapse reaction and useful alleviation.

Gen would likewise be utilized on aspiring AI extends beneath the Massachusetts Institute of Technology quest after Intelligence. Massachusetts Institute of Technology scientists have buckled down and tried to contour AI profound learning for novices or beginners. it's been easy for them to unite distinctive AI systems and work on all of them things thought-about.

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