#bigdata 37e — Big Data Applications: Internet of Things (Part IV)
Article Parts:
PART I — Big Data Applications: Users, Google and Netflix
PART II — Big Data Applications: Amazon andTesla
PART IV — Big Data on Internet of Things (IoT)
The Internet of Things (IoT) is one of the most promising areas for Big Data applications.
The IoT connects any “thing” that generates data to Internet: devices, wearables, video games, cars, appliances, satellites, aircraft, in short, a whole range of sensors and devices, generating data without stopping.
Industry experts have identified IoT as the next Industrial Revolution or the next Internet, believing that it is the future form of the physical world interaction between government, business, and consumers.
It is possible that the number of connected devices worldwide will reach 50 billion in 2020 and investments in IoT will be $267 billion this year.
According to Ericsson, the IoT will surpass the smartphone as the largest category of connected devices in 2018.
It is possible that IoT will become the most significant application area of Big Data, or at least require a more considerable investment of resources and the attention of companies.
Business advantages with IoT
IoT is in its infancy but will impact companies considering the speed that is transforming the Big Data market.
Companies can take advantage of IoT, getting a more comprehensive and sophisticated intelligence to better understand preferences, behaviors, and feelings of the client.
With more data volumes, companies get more intelligence and can discover more elements to be explored to improve business performance, saving time and money.
IoT provides faster and more flexible data analysis and increases the ROI of companies that are looking for robust strategies of IoT to implement.
The so-called “bots” (scripts and automated programs) and Machine Learning, combined in an automated architecture with the power of Big Data analysis, can provide immeasurable value to the business.
IoT brings greater operational efficiency primarily to the operations of the supply chain, an appropriate area for the use of this technology, where the IoT ecosystem maps the effectiveness of existing processes in detail and uses this information to reduce cost structures.
Examples of IoT applications
Some applications of IoT implemented with Big Data are:
1 — Energy Power Management
The economy of energy consumption requires sensors gathering data on their use and sending for analysis of Big Data.
Individual devices can collect data in real time from buildings and machines to which they are connected.
This information can be cleaned, consolidated, and shared with energy providers to more efficiently utilize energy in buildings.
That will decrease public utility costs, improving the quality of life of residents.
2 — Military Operations
Sensors can be included with weapons, transport equipment, and other war machines.
The collected data of these devices allow preventive maintenance and maintenance schedules, based on past trends.
In this way, the military can work with the highest possible security and the lowest cost.
3 — Health
IoT brings disruption to healthcare, transforming modern medicine into something more simple, practical and inexpensive.
That allows physicians to deal with patients in remote locations, online monitor the health of the elderly, evaluating glucose levels, prevent heart attacks, and get a complete historical patient for years in comparative graphs.
IoT may permit providers and health networks the ability to monitor and manage centrally locally, increasing efficiency, effectiveness and quality of care.
The application of the IoT in health is delightful because it affects us potentially to diagnose, treat and prevent diseases more efficiently, and save countless lives.
4 — Sport
IoT is revolutionizing the sport. It became a means of obtaining detailed information about the condition of an athlete before, during and after a game.
The data management tools can be utilized to combine datasets from doctors, physiotherapists, sports scientists and other sources.
Data collected from IoT devices can mitigate the risks related to sports injuries, and help teams compete more effectively.
Predictive analytics are applied to the data to anticipate future performance of an athlete in competition as well as its potential longevity.
5 — Aviation
One of the areas of use of IoT is in aviation, with hundreds of sensors detecting mechanical anomalies in real time.
An internet of Things devices is used to avoid delays and keep passengers safe, sensors to monitor the movement of baggage, instruments to control the cabin pressure, temperature and other services on board.
6 — Virtual Assistants
You probably heard a lot about some of these virtual assistants like Siri Apple, Amazon’s Alexa, Google and Microsoft Cortana Wizard.
These virtual assistants use voice recognition and provide answers from a variety of commands such as play music, read the news, set alarms, control appliances, order a pizza and pay bills.
Many companies are discovering these virtual assistants to send meeting reminders, provide instructions for events, share data to other applications and many other uses.
Predictive analytics can be applied to search for patterns and trends in data from these devices, discovering which factors have more influence on the results and anticipate what is likely to occur based on current and historical information about the device.
We can identify the musical taste of a hotel guest, or the level of interest in the weather forecast or movie listings. Data collected by virtual assistants can be beneficial for improving enterprise business.
Conclusions
As grows the use of IoT, increasing volumes of data, and raises more and more the importance of Big Data applications.
The data are of genuine importance for the survival of companies, and consequently, it is time to give attention and significance to them, considering its context, interpretation, and value of the IoT strategy.
CURIOSITIES
- Organizations that embark on IoT for the first time are required to pay close attention to the quality of information and data integrity.
- Smart sensors are primary objects to collect data on IoT.
- One of the sensors used in most IoT applications is RFID (radio frequency identification), which is a tag, a transponder, a small object that can be put on a person’s skin, animal, equipment, or product packaging, among others.
- Supermarket products with RFID tags remove the payment in boxes with human service.
- Smart houses use IoT remotely control lighting systems, surveillance, curtain opening and closing, and water temperature, among others.
More information about this article
Article selected from the eBook “Big Data for Executives and Market Professionals.”
Apple Books: Author Page
Amazon Books: Author Page
Kobo: English Version or Portuguese Version
