How Big Data Analytics Make Cities Smarter?

Smart city and big data

There has been a lot of activity around the concept of Smart City for some time. Cities are being identified as future smart cities. Theoretically at least, smart cities can fundamentally change our lives at many levels such as less pollution, garbage, parking problems and more energy savings. Though the prospect seems mouth-watering, the implementation of the smart city concept around the world has been sporadic at best because of several reasons. Whatever the stage the smart city implementation is at globally, big data and the Internet of Things (IoT) have the power to drive the implementation.

Undoubtedly, the main strength of the big data concept is the high influence it will have on numerous aspects of a smart city and consequently on people’s lives. Big data is growing rapidly, currently at a projected rate of 40 % growth in the amount of global data generated per year versus only 5 % growth in global IT spending. Around 90 % of the world’s digitized data was captured over just the past two years. As a result, many governments have started to utilize big data to support the development and sustainability of smart cities around the world. That allowed cities to maintain standards, principles, and requirements of the applications of smart city through realizing the main smart city characteristics. These characteristics include sustainability, resilience, governance, enhanced quality of life, and intelligent management of natural resources and city facilities.

Big Data in Smart Cities

If major cities were to invest into smart transport systems today, then by 2030 they would save around $800 billion annually. On top of that, smart transport systems also contribute in a few other ways, including:
  • Less automobile congestion and fewer accidents
  • More advancements in faster long distance travel
  • Clean air from the reduction of pollution
  • Excess of new jobs from updates in transportation networks
  • Furthermore, any upgraded transportation option appeals to established businesses looking for a new locale, as they do to startup businesses. Any business wants to know that their workers and clients have access to efficient modern transportation. That access lowers annual budgets for businesses in terms of what they pay in gas mileage and delivery costs.


Big data tracks transportation infrastructure needs and costs helping cities define ways to expand their public transport options in the most efficient way possible. It defines what areas of the city need to open up and how receptive people are about initiatives to raise money for such a project. Cities that use this type of big data analytics are called smart cities and much of the world wants in on the innovations.

Many major cities are starting to use INRIX, a system that analyzes data from traditional road sensor networks and mobile device data. San Francisco’s Metropolitan Transportation Commission saved over $250,000 per year from the direct data collection of INRIX. 

Big Data in Law Enforcement


Contrary to popular belief, in terms of fighting crime, big data is actually allowing police and other law enforcement officers to behave less like Big Brother than more. Data analytics allows law enforcement officers to track real trouble spots and dangerous criminals.



Many local agencies are starting to use PREDPOL or predictive policing systems that collect three main data points from every report: type of crime, location and time of the incident, to make accurate officer deployment decisions in the future.


PREDPOOL


Once high criminal activities are identified, new education initiatives and outreach programs can be utilized in those jurisdictions.


Big Data in Education

The collection and analysis of big data helps educators understand which students need help, why they need help as well as identifying areas in which they excel.

Educators can provide relevant individual and group activities to support each student’s goals and needs. Teachers will be able to assess student progress on a consistent basis in order to challenge students and help them grow.

The analytics provide more three-dimensional insights of their students’ progress while allowing parents a way to understand how each child learns. 
AltSchool is one of the first K-8th grade school providing this personalized learning experience which is only available in developing smart cities such as San Francisco and New York.

altschool

The introduction of big data in the education space has encouraged students of all ages to learn remotely in the comfort of their homes. These massive open online courses collect data from millions of course takers and analyze it to find trouble areas that are causing students to fail. After analyzing millions of data points, algorithms continually updated each course to deliver an “adaptive learning experience” based on each individual’s strength, weaknesses and preferences.

These are just two examples of the many ways smart cities are adapting schools into more personalized and remote learning platforms which may change the learning experience forever.

Big Data in Health

The United Nations says that by 2050, 66% of the world’s population will be considered urban. With populations living in such close proximities, this means that health initiatives must be available to everyone no matter their background, race or economic status.

Big data can already predict the outbreaks of viruses and even track cases of depression. Smart cities will use millions of sensors that provide personalized medical services. Many citizens of smart cities will be able to activate their medical service by a mobile app or free standing kiosks throughout the city. Pulsepoint Respond is a great example of a personalized app that alerts CPR-trained bystanders of sudden cardiac arrests within their immediate area.

PlusPoint
On top of that, smart cities have already started testing systems that allow elderly patients the option to remain in their homes instead of at a nursing care facility. These type of systems include a standalone table, a tablet with Skype and wireless home sensors used for video communication between the patient and their remote caregiver.

The wireless sensors monitor the house and send alerts about safety situations such as a left-on stove or doors opening in the middle of the night. After testing this system in Oslo, Norway, the study has shown that the system can save $85,000 for each person since they don’t have to move into a nursing facility.

Big Data in Energy Usage.

Over 75% of the world’s energy consumption come from cities and 40% of municipal energy cost come solely from street lighting. Since adopting smart street lights which automatically adjust light levels to suit the needs of citizens, Lansing, Michigan saved 70% of their energy cost.

Experts predict that by 2020 there will be over 100 million of these smart light bulbs and lam>s used worldwide. Other cities like Charlotte, North Carolina have implemented smart building energy management which cut their total energy use by 8.4% and greenhouse gas emissions by 20%.

Moreover, the Spanish town of Santander installed 12,500 air pollution and RFID sensors around the city which diminished energy costs by 25% and waste management cost by an additional 20%. Smart cities are barely underway, yet they are already making substantial impact on the environment and to the citizens living in them.

Masdar City in Abu Dhabi and Songdo in South Korea are prime examples of connected cities that, using a local energy optimisation system, materialise the promises of a zero emission, zero waste model. All of the data from the sensors, spread throughout the city, are analysed in real time to optimise a number of aspects of inhabitants' lives.


Want to learn Digital Marketing?

Popular posts from this blog

MongoDB - daTa ModeLLinG Concepts: SQL - Where all to UsE ?

Comparing Bootstrap With Google's Material Design Lite : Bootstrap - ResponSive Design

MongoDB overView with Installation_procEss: SQL - Where all to UsE ?