Showing posts with label Intelligent Transportation. Show all posts
Showing posts with label Intelligent Transportation. Show all posts

AI - Smart Homes And Smart Cities.

 



Projects to develop the infrastructure for smart cities and houses are involving public authorities, professionals, businessmen, and residents all around the world.


These smart cities and houses make use of information and communication technology (ICT) to enhance quality of life, local and regional economies, urban planning and transportation, and government.


Urban informatics is a new area that gathers data, analyzes patterns and trends, and utilizes the information to implement new ICT in smart cities.

Data may be gathered from a number of different sources.

Surveillance cameras, smart cards, internet of things sensor networks, smart phones, RFID tags, and smart meters are just a few examples.

In real time, any kind of data may be captured.

Passenger occupancy and flow may be used to obtain data on mass transit utilization.

Road sensors can count cars on the road or in parking lots.



They may also use urban machine vision technologies to determine individual wait times for local government services.


From public thoroughfares and sidewalks, license plate numbers and people's faces may be identified and documented.

Tickets may be issued, and statistics on crime can be gathered.

The information gathered in this manner may be compared to other big datasets on neighborhood income, racial and ethnic mix, utility reliability statistics, and air and water quality indices.



Artificial intelligence (AI) may be used to build or improve city infrastructure.




Stop signal frequencies at crossings are adjusted and optimized based on data acquired regarding traffic movements.


This is known as intelligent traffic signaling, and it has been found to cut travel and wait times, as well as fuel consumption, significantly.

Smart parking structures assist cars in quickly locating available parking spaces.


Law enforcement is using license plate identification and face recognition technologies to locate suspects and witnesses at crime scenes.

Shotspotter, a business that triangulates the position of gunshots using a sensor network placed in special streetlights, tracked and informed police agencies to over 75,000 bullets fired in 2018.

Information on traffic and pedestrian deaths is also being mined via big data initiatives.

Vision Zero is a global highway safety initiative that aspires to decrease road fatalities to zero.

Data analysis using algorithms has resulted in road safety efforts as well as road redesign that has saved lives.



Cities have also been able to respond more swiftly to severe weather occurrences because to ubiquitous sensor technology.


In Seattle, for example, conventional radar data is combined with RainWatch, a network of rain gauges.

Residents get warnings from the system, and maintenance staff are alerted to possible problem places.

Transport interconnection enabling completely autonomous autos is one long-term aim for smart cities.

At best, today's autonomous cars can monitor their surroundings to make judgments and avoid crashes with other vehicles and numerous road hazards.

However, cars that connect with one another in several directions are likely to create fully autonomous driving systems.

Collisions are not only averted, but also prevented in these systems.


Smart cities are often mentioned in conjunction with smart economy initiatives and foreign investment development by planners.


Data-driven entrepreneurial innovation, as well as productivity analyses and evaluation, might be indicators of sensible economic initiatives.

Some smart towns want to emulate Silicon Valley's success.

Neom, Saudi Arabia, is one such project.

It is a proposed megacity city that is expected to cost half a trillion dollars to build.

Artificial intelligence is seen as the new oil in the city's ambitions, despite sponsorship by Saudi Aramco, the state-owned petroleum giant.

Everything will be controlled by interconnected computer equipment and future artificial intelligence decision-making, from home technology to transportation networks and electronic medical record distribution.


One of Saudi Arabia's most significant cultural activities—monitoring the density and pace of pilgrims around the Kaaba in Mecca—has already been entrusted to AI vision technologies.

The AI is intended to avert a disaster on the scale of the 2015 Mina Stampede, which claimed the lives of 2,000 pilgrims.

The use of highly data-driven and targeted public services is another trademark of smart city programs.

Information-driven agencies are frequently referred to as "smart" or "e-government" when they work together.


Open data projects to encourage openness and shared engagement in local decision-making might be part of smart governance.


Local governments will collaborate with contractors to develop smart utility networks for the provision of electricity, telecommunications, and the internet.

Waste bins are linked to the global positioning system and cloud servers, alerting vehicles when garbage is ready for pickup, allowing for smart waste management and recycling initiatives in Barcelona.

Lamp poles have been converted into community wi-fi hotspots or mesh networks in certain areas to provide pedestrians with dynamic lighting safety.

Forest City in Malaysia, Eko Atlantic in Nigeria, Hope City in Ghana, Kigamboni New City in Tanzania, and Diamniadio Lake City in Senegal are among the high-tech centres proposed or under development.


Artificial intelligence is predicted to be the brain of the smart city in the future.


Artificial intelligence will personalize city experiences to match the demands of specific inhabitants or tourists.

Through customized glasses or heads-up displays, augmented systems may give virtual signs or navigational information.

Based on previous use and location data, intelligent smartphone agents are already capable of predicting user movements.


Artificial intelligence technologies are used in smart homes in a similar way.


Google Home and other smart hubs now integrate with over 5,000 different types of smart gadgets sold by 400 firms to create intelligent environments in people's homes.

Amazon Echo is Google Home's main rival.

These kinds of technologies can regulate heating, ventilation, and air conditioning, as well as lighting and security, as well as household products like smart pet feeders.

In the early 2000s, game-changing developments in home robotics led to widespread consumer acceptance of iRobot's Roomba vacuum cleaner.

Obsolescence, proprietary protocols, fragmented platforms and interoperability issues, and unequal technological standards have all plagued such systems in the past.


Machine learning is being pushed forward by smart houses.


Smart technology' analytical and predictive capabilities are generally regarded as the backbone of one of the most rapidly developing and disruptive commercial sectors: home automation.

To function properly, the smarter connected home of the future needs collect fresh data on a regular basis in order to develop.

Smart houses continually monitor the interior environment and use aggregated past data to establish settings and functionalities in buildings with smart components installed.

Smart houses may one day anticipate their owners' requirements, such as automatically changing blinds as the sun and clouds move across the sky.

A smart house may produce a cup of coffee at precisely the correct time, order Chinese takeout, or play music based on the resident's mood as detected by emotion detectors.


Pervasive, sophisticated technologies are used in smart city and household AI systems.


The benefits of smart cities are many.

Smart cities pique people's curiosity because of its promise for increased efficiency and convenience.

It's enticing to live in a city that anticipates and easily fulfills personal wants.

Smart cities, however, are not without their detractors.

Smart havens, if left uncontrolled, have the ability to cause major privacy invasion via continuous video recording and microphones.

Google contractors might listen to recordings of exchanges with users of its famous Google Assistant artificial intelligence system, according to reports in 2019.


The influence of smart cities and households on the environment is yet unknown.


Biodiversity considerations are often ignored in smart city ideas.


Critical habitat is routinely destroyed in order to create space for the new cities that tech entrepreneurs and government officials desire.

Conventional fossil-fuel transportation methods continue to reign supreme in smart cities.

The future viability of smart homes is likewise up in the air.

A recent research in Finland found that improved metering and consumption monitoring did not successfully cut smart home power use.


In reality, numerous smart cities that were built from the ground up are now almost completely empty.


Many years after their initial construction, China's so-called ghost cities, such as Ordos Kangbashi, have attained occupancy levels of one-third of all housing units.

Despite direct, automated vacuum waste collection tubes in individual apartments and building elevators timed to the arrival of residents' automobiles, Songdo, Korea, an early "city in a box," has not lived up to promises.


Smart cities are often portrayed as impersonal, elitist, and costly, which is the polar opposite of what the creators intended.

Songdo exemplifies the smart city trend in many aspects, with its underpinning structure of ubiquitous computing technologies that power everything from transportation systems to social networking channels.

The unrivaled integration and synchronization of services is made possible by the coordination of all devices.

As a result, by turning the city into an electronic panopticon or surveillance state for observing and controlling residents, the city simultaneously weakens the protective advantages of anonymity in public settings.


Authorities studying smart city infrastructures are now fully aware of the computational biases of proactive and predictive policing.



~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram


You may also want to read more about Artificial Intelligence here.



See also: 

Biometric Privacy and Security; Biometric Technology; Driverless Cars and Trucks; Intelligent Transportation; Smart Hotel Rooms.


References & Further Reading:


Albino, Vito, Umberto Berardi, and Rosa Maria Dangelico. 2015. “Smart Cities: Definitions, Dimensions, Performance, and Initiatives.” Journal of Urban Technology 22, no. 1: 3–21.

Batty, Michael, et al. 2012. “Smart Cities of the Future.” European Physical Journal Special Topics 214, no. 1: 481–518.

Friedman, Avi. 2018. Smart Homes and Communities. Mulgrave, Victoria, Australia: Images Publishing.

Miller, Michael. 2015. The Internet of Things: How Smart TVs, Smart Cars, Smart Homes, and Smart Cities Are Changing the World. Indianapolis: Que.

Shepard, Mark. 2011. Sentient City: Ubiquitous Computing, Architecture, and the Future of Urban Space. New York: Architectural League of New York.

Townsend, Antony. 2013. Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. New York: W. W. Norton & Company.





Artificial Intelligence - How Is AI Being Applied To Air Traffic Control?

 


Air Traffic Control (ATC) is a ground-based air navigation service that directs airplanes on the ground and in regulated airspace.

Air traffic controllers also give advising services in uncontrolled airspace on occasion.

By coordinating the movement of commercial and private planes and guaranteeing a safe separation of traffic in the air and on the ground, controllers ensure the safe flow of air traffic.

They usually provide pilots with real-time traffic and weather notifications along with directing guidance.

The major goals of the ATC, according to the Federal Aviation Administration (FAA), are to manage and expedite air traffic flow, as well as to prevent aircraft crashes and provide real-time information and other navigational assistance for pilots.

The ATC is a service that is both risk adverse and safety crucial.

Air traffic controllers use a variety of technology, including computer systems, radars, and transmitters, in addition to their eye observation.

The volume and density of air travel has been increasing over the world.

The operational boundaries of modern ATC systems are being pushed as worldwide air traffic density increases.

To keep up with the rising need for accommodating future expansion in air traffic, air navigation and air traffic management systems must become increasingly complex.

Artificial intelligence (AI) provides a number of applications for safer, more efficient, and better management of rising air traffic.

According to the International Civil Aviation Organization's (ICAO) Global Air Navigation Plan (GANP), AI-based air traffic management systems may help address the operational issues posed by the growing volume and variety of air traffic.

Simulation systems with AI that can monitor and advise the activities of trainee controllers are already used in the training of human air traffic controllers.

In terms of operations, the ability of machine learning-based AI systems to ingest massive amounts of data may be used to solve the complexity and challenges of traffic management.

Such technologies may be used to assess traffic data for flight planning and route selection during the planning stages.

By detecting a wide range of flight patterns, AI can also provide reliable traffic predictions.

AI-based ATC systems may be used for route prediction and decision-making in en route operations, particularly in difficult scenarios with little data.

AI can help with taxiing methods and runway layouts.

Additionally, AI-assisted voice recognition technologies may help pilots and controllers communicate more effectively.

With such a wide range of applications, AI technologies may help human air traffic controllers improve their overall performance by providing them with detailed information and quick decision-making procedures.

It's also worth noting that, rather than replacing human air traffic controllers, AI-based solutions have shown to be useful in ensuring the safe and efficient flow of air traffic.


~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.



See also: Intelligent Transportation.


Further Reading

Federal Aviation Administration. 2013. Aeronautical Information Manual: Official Guide to Basic Flight Information and ATC Procedures. Washington, DC: FAA. https://www.faa.gov/air_traffic/publications/.

International Civil Aviation Organization. 2018. “Potential of Artificial Intelligence (AI) in Air Traffic Management (ATM).” In Thirteenth Air Navigation Conference, 1–3. Montreal, Canada. https://www.icao.int/Meetings/anconf13/Documents/WP/wp_232_en.pdf.

Nolan, Michael S. 1999. Fundamentals of Air Traffic Control. Pacific Grove, CA: Brooks/Cole.





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