How to Manage Data Generated by the Internet of Things (IoT)?

As new uses are developed and the cost of sensors decreases, more and more internet-connected objects are being used and sold by companies. Between the improvement of processes and the creation of innovative services, the Internet of Things is revolutionizing many fields of activity.
But “connected objects” is also a synonym of “real-time data collection“: a major issue for organizations, which see brand new opportunities in this technology.

What is the Internet of Things (IoT)?

The Internet was initially restricted to computers. It then spread to other devices, such as smartphones and tablets. But today, all types of objects can be connected to the web: watches, cars, household appliances, televisions, and industrial machines… This new paradigm is called the Internet of Things, or IoT.
The secret of this technology? Sensors and chips which allow a wide variety of devices to be connected, bringing along with them a host of new functionalities. It is now possible to browse the web with a watch, something that was unthinkable just a few years ago.
In addition to the connectivity itself, the IoT is characterized by its capacity for data collection. So a smartwatch not only allows access to the Internet, it is also capable of collecting all sorts of information about its wearer: heart rate, number of steps taken during the day, etc. But far from being a simple collection of gadgets, the IoT has very concrete applications in various fields.

The Primary Applications of the IoT

The IoT marketplace is booming, thanks in particular to the development of onboard electronics, which allows for the collection and processing of large amounts of data. The potential of the IoT soon attracted the attention of several business sectors, which are now using it in a multitude of ways.
In general, connected objects are used in three main segments.

The “Consumer” Segment

This is undoubtedly the aspect of the IoT that is most familiar to the general public. In fact, connected objects have entered consumers’ daily lives in a variety of forms. Portable technologies, such as the connected watches mentioned above, are a prime example of this.
But the Internet of Things is also reflected in the concept of the “smart home”. The intelligent and connected home utilizes home automation, which permits the mechanization of many tasks. From the opening of doors and shutters to automatic heating control and the watering of gardens… the possibilities are endless.

Consumers have found many uses for the IoT when it comes to comfort, safety and energy savings. But the sensors in a smart home are also fantastic data collection tools. This is valuable data for manufacturers, who analyze it in order to better understand the needs and practices of their users.
This data can be stored in its “raw” form, usually on a platform connected to the Cloud, and subsequently studied in-depth. The data can also be partially processed before being stored, thanks to certain algorithms already installed on the connected objects.

The Commercial Segment

Smart homes don’t have a monopoly on IoT—far from it! Beyond the home, connected objects can be found everywhere people live and travel: offices, shopping centers, stores, hotels, hospitals, and community centers. This multitude of applications for the Internet of Things permits the collection of environmental data, the management of access and scheduling within companies, and improvements in product traceability.

The retail sector was also quick to adopt the IoT, finding in it new ways to optimize its processes. Logistics, in particular, were optimized, both in terms of warehousing and transportation. With the help of sensors, it is possible to obtain a comprehensive picture of the movement of merchandise from the production line to the store shelves and then on to the customer.
It is also possible to analyze detailed information, such as the amount of time a product spends in transit or its storage temperature. It is even possible to interact with a product in real time. This technology is particularly useful when it comes to transporting perishable goods, allowing retailers to act quickly in the case of fluctuating temperatures or food spoilage.

See also :

Data: a valuable asset for your supply chain

The Industrial Segment

Industry adopted the Internet of Things very early on, recognizing in it the potential for increased efficiency and productivity.
Indeed, today’s factories are using IoT-compatible machines to work smarter. With automated industrial systems equipped with sensors, it is possible to more accurately map not only workloads, but also the inputs and outputs of each individual machine.
Manufacturers can also monitor machine wear more closely, leading to predictive rather than reactive maintenance. This has the advantage of increasing durability, thereby reducing the lifecycle costs of machines. These functionalities, which result in increasingly automated and connected factories, are at the heart of Industry 4.0.
Thanks to the advent of “machine to machine” (M2M), machines are now able to interact with each other without human intervention and subsequently combine the resulting data into a single flow. This allows for machines to be monitored in real time, and for data to be easily traced back to the storage platform for further processing.

IoT and Data: multiple challenges

According to the 451 Research Institute, there were eight billion connected objects in the world in 2019. This figure is expected to reach 13.8 billion by 2024. As the number of connected objects increases, the amount of data generated by the IoT explodes.
The management and analysis of all this data poses a major challenge in the coming years. Firstly, it is necessary to improve the connection of IoT devices and platforms to the Cloud, as well as to existing systems that businesses have in use. But companies must also focus on the most relevant objects, sensors and data. Otherwise, they put themselves at risk of being quickly overwhelmed…
Advanced analytical tools are essential to the efficient processing of the immense volume of data generated by connected objects… These analytical tools are also indispensable in extracting qualitative and truly usable information from the data. A carefully calibrated blend of Big Data and machine learning allows for the detection of recurring patterns within the data. Models that are particularly useful for different applications, such as predictive maintenance.
Another major challenge for the Internet of Things : the reliability of sensors, which play an increasingly important role. All efforts made to improve data processing will be in vain if the baseline data is of poor quality.

DigDash: Ideal tools for managing and processing IoT data

As we have seen, the exploitation of data generated by the Internet of Things presents many obstacles. Business Intelligence and data visualization tools are more useful than ever.
In this context, DigDash supports a number of companies in recovering their IoT data. For example, a start-up selling connected bracelets was able to generate KPIs from the global data of its users.
In the commercial and industrial fields, on the other hand, the entire lower part of data recovery (analog or digital) from sensors remains and will remain linked to existing systems. Why? For both security reasons, and to allow tracking and real-time interaction with the data. However, the explosion of data derived from the IoT necessitates powerful tools at a variety of levels.


Arcure and DigDash improve industrial security with IoT

Developed by Arcure, the Blaxtair Connect system can detect obstacles and pedestrians, considerably reducing the risk of collision of industrial and construction machinery. True connected objects, whose data can be analyzed using a dashboard designed with DigDash Enterprise, in order to take preventive measures and avoid future accidents.


Indeed, IoT solutions force businesses to manage new kinds of data, generated and hosted on different platforms. According to Gartner, 68% of companies implementing IoT consider data security and quality to be a priority. A difficult goal to achieve, given the volume and complexity of the data involved. As an overview, DigDash Enterprise is positioned as an adapted management tool, allowing for easy visualization and exploration of data, even in large quantities.
Another major issue: according to Gartner, 67% of organizations focus on aggregating IoT and “traditional” data. Indeed, the capacity to create a “data mix” is crucial to optimizing the use and management of data.
It is also important to be able to reconcile the different sources of purely IoT data, which vary significantly. Certain industrial machines are equipped with sensors that operate 24 hours a day, while the sensors of other machines are activated intermittently.
Finally, this global approach has become essential due to increasing needs for prediction, performance, and consumption. The data generated by the IoT must move away from the factory floor and processes, and towards a centralized platform.

The Internet of Things has immense potential and already has multiple applications in all sectors. However, the recovery and processing of IoT data presents significant challenges. The DigDash Enterprise platform is a powerful tool, providing centralized management of data generated by all types of IoT devices.