Innovative ideas always gain traction and cannot be withheld as they expand across countries and eventually the globe. The process of moving forward exemplifies the survival of humanity, even though recent technologies have drastically changed our methods of forward momentum.
Today, the progressive revolution can be seen all around, especially with the adaptation of big data within our daily lives. Our civilization can algorithmically process massive amounts of data to provide us a detailed understanding of our choosing.
As the interlacing of big data and IoT get stronger, this will only improve our standards of living, create sustainable efficiency and cultivate smart cities in a number of significant ways.
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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.
So the 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. The Baltimore Metropolitan Council saved $25,000 per year in fuel and labor cost because of increased efficiency.
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.
Once high criminal activities are identified, new education initiatives and outreach programs can be utilized in those jurisdictions.
Since using PREDPOL, the town of Reading, Pennsylvania, has seen crime drop to the lowest rate in over 35 years with a 19% drop in violent crimes and a staggering 44% drop in burglaries. Santa Cruz, California, saw similar result with their first as burglaries dropped by 11% and robberies drop by 27%.
Besides predictive policing, the FBI invested 1 billion dollars into a next generation identification system which uses a combination of DNA, fingerprints, 3D facial photos and voice recognition to pinpoint criminals. As smart cities start to implement these systems into their infrastructure, crimes will be mapped before they even happen and criminals can be identified within seconds.
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.
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.
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, 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
If implemented on a wide scale, smart energy efficiency systems could save the United States more than $1.2 trillion by using IoT devices and big data analytics.
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 lamps 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.
The 2025 Forecast
Some experts believe that cities could be investing nearly $400 billion a year building smart cities in the next 5 years. The government has even launched a smart city initiative to help communities tackle local challenges and improve city services.
All industries can expect to see a boom as people become healthier and live longer which will ultimately cause new demands for food and housing production.
Past traditional methods will supply very little of our production because big data and smart technologies has already started making monumental impacts on our way of life and growth of civilization.
Editor’s note: This is a post written by Andrew Deen for Hongkiat.com. Andrew has been a consultant for startups in almost every industry from retail to medical devices. He implements lean methodology and is currently writing a book about scaling up businesses. Contact Andrew on Twitter.