IoT and Big Data: Understanding the Relationship between These Two Technologies
The Internet of Things (or IoT) and Big Data are two interconnected and inseparable technologies. More and more devices and objects are connected to the Internet. These connected objects generate data, which can be analyzed to reveal trends and information for various purposes. This is why Big Data and the Internet of Things (IoT) are closely related. However, before going into more detail about this relationship, we need to go back to the definition of these two technologies.
What is IoT?
For several years now, Internet has not been limited to computers and other smartphones. Now almost all objects are connectable to the Internet. Watches, fridges, televisions, cars, or industrial machines … the Internet of Things have no limits.
Connected objects rely on embedded chips and sensors that connect them to the Internet and give them new features. For this, companies operate different communication networks. Some use cellular technologies, others use free frequency bands. This is not the main subject. Indeed, the utility of these electronic components is to collect data.
For example, a connected watch is able to count the steps of its wearer, or measure its heart rate. Similarly, sensors embedded by a connected machine to measure its performance, or to predict possible failures.
What is Big Data?
The term Big Data refers to information that has three main characteristics: velocity, variety, and volume. This is therefore a large amount of structured or unstructured data. Velocity refers to the processing speed of these data.
The main feature of Big Data, however, is the ability to analyze them in order to extract actionable information.
IoT and Big Data: two inextricably linked technologies
As the number of connected objects increases, the volume of data generated by the Internet of Things explodes. Thus, to be able to support and analyze them in real time, it is necessary to rely on Big Data analytical tools.
These tools have the ability to quickly process the large volumes of data continuously generated by IoT devices, and extract actionable insights. The machine learning makes it possible to locate data models. With these patterns, a company can implement predictive maintenance on its industrial machines.
IoT and Big Data: some examples of use cases
To illustrate the correlation between IoT and Big Data, we can take the example of transport companies. These utilize the data collected by sensors and Big Data analytics tools to improve efficiency, save money, and reduce their impact on the environment.
The delivery vehicles have sensors that monitor the engine condition, the number of stops, the speed of travel, the number of kilometers traveled or the amount of fuel consumed.
IoT and Big Data are also used in agriculture. For example, operators place sensors in the fields to measure the humidity level and transmit the data to a central system. Thus, it is possible for them to know when plantations reach their optimal moisture level.
For their part, consumers want to take advantage of the smart home concept. The connected house is not only a place where most controls (opening / closing of the flywheels, heating and lighting control, purchase of automated consumables, etc.) are automatized, but also a place where we analyze consumer data. It is for the owner to reduce his energy bill or to analyze his sleep. For connected device manufacturers and service providers, understanding user needs makes it easier to target advertising, deliver relevant services, or design new products.
IoT and Big Data: challenges and opportunities
By 2020, Gartner estimates that about 20.8 billion connected objects will be used worldwide. The resulting increase in the volume of data will provide new opportunities, but will also create obstacles to overcome. Generating billions of dollars with IoT is not as easy as some might think.
The cybersecurity is one of the challenges to the development of IoT and Big Data . Hackers covet more and more computer systems. Indeed, they host critical data on which connected objects are based. For example, the emergence of “smart cities” or connected cities could allow cybercriminals to take control of an entire city.
