IoT and Big Data: Understanding the relationship between these two technologies
Today, technological advances are gaining momentum in the lives of users, but also in the world of business, health, industry, and the military. One of the most promising technologies is the IOT, or Internet of Things, which will allow physical objects to connect to the Internet, thus optimizing their functioning by generating data. However, in a world where data is becoming king, it must be handled efficiently and the means of IT must allow to store an ever-increasing number of data. This is where Big Data takes on its importance.
The IoT: definition
The Internet of Things (IoT) is a concept that connects physical or virtual objects to the internet. The technology very often used is the sensor, allowing to link a physical object such as a watch, a drone or even a speaker, to the internet. If for a long time the few objects connected to the Internet were the telephone and the computer, this is no longer the case today and every year new types of objects incorporating IOT technology are born.
Each IOT has 5 common and inseparable components for the functionality of it. These are:
- Sensors: connecting the physical object to different computer systems;
- Connectivity: the network is essential to connect the object to the Internet (Wifi, wired, 4G or 5G…);
- Data: The main purpose of IOT is to collect and transmit data;
- Information: Translating data into information is essential to be able to read and then exploit the data;
- Operating applications: allowing you to control IOTs but also to read the information you receive.
IOT is one of the greatest technological revolutions of our era and its potential for exploitation is immense. IOT could have a huge impact on the cars of the future or on the new versions of smart-cities, an urban space connected to the Internet, thus significantly improving the lives of users, while reducing the negative impact of these on the planet.
The definition of Big Data
Big Data refers to a massive set of data that no conventional data management tool can handle. Big Data is therefore a concept that allows access to gigantic databases in real time. It has three main features:
- The speed at which information is processed;
- The variety of information stored (in the form of processed or unprocessed data from a variety of sources);
- The volume of information listed.
Big Data’s main objectives are to improve a company’s or system’s responsiveness to a large amount of data collected, increase productivity and refine knowledge of customer behavior, so that it can offer personalized offers or advertisements and create new trends.
Relationship between Big Data and IOT
According to several studies, the use of IOT is expected to generate 4.4 trillion GBytes in 2020, and this figure is expected to increase in subsequent years. In addition, this data must be read, exploited and transmitted within specific timeslots, so, as you might have guessed, the major challenge in the field of the Internet of Things is to be able to exploit a huge amount of data, hence the use of big data.
What is the role of Big Data in IoT?
Big Data should enable real-time analysis of the data generated by IOT and thus optimize the use of this technology. To do this, Big Data proceeds in four steps:
- Collecting data generated by IoT by following the three primary principles of Big Data: speed, volume and variety;
- Storing data in files within the Big Data database;
- Data analysis by complex and efficient analytical systems, such as Spark or Hadoop;
- The implementation of the report of the analyzed data.
Big Data will play an important role in information processing efficiency and will enable IoT developers to optimize these tools to broaden the current perspective.
How do IoT and Big Data interact together?
The interaction between IoT and Big Data is not one-way. IoT could also bring a lot to Big Data. The more important IoT are in your daily life and that of your city, the more developers will be demanding greater capacity in terms of big data and the more this business will grow.
It will thereby be important to improve data storage technologies to develop systems capable of processing even more data. This interaction could thus enable technological growth in both areas simultaneously.
Examples of use cases
Here are 2 examples of areas where the combination of Big Data and the Internet of Things could have an innovative impact:
- Business: in business areas, the combination of IoT and Big Data can dramatically transform business marketing. The massive collection of data and the processing of it could give real added value to the business world, to obtain optimal commercial Companiesare increasingly storing their data in more operational and cost-effective Big Data Clouds;
- Health: Having to diagnose diseases remotely with optimal reliability might make you think of a futuristic film scenario, however, this is one of the major health issues of IoT. The research focuses on ways to remotely generate diagnostics and care systems. Big Data will enable highly efficient processing of data from IoT sensors on many physical objects, to enable a better understanding of diseases.
Data security, the Achilles’ heel of these technologies
Cyber security is one of the biggest, if not the biggest, challenges of these technologies. Data tends to become the new black gold and it is becoming more and more coveted in a lot of areas, such as marketing for example.
While the issue of data privacy should become even more prominent in the public debate, the issue of data protection against cybercrime must also be taken seriously.
The more systems are connected to the Internet, the more they become a prime prey for hackers. For example, with the emergence of smart cities, hackers could take control of an entire city, if not more.
IoT and Big Data are two independent technologies that are inseparable from each other, to enable well-known technological advances. While the IoT would largely collect data from physical objects through different sensors, Big Data would allow faster and more efficient storage and processing of this data.