The Internet of Things exists thanks to the increasing number of new, internet-connected smart devices. These devices create behavioral logs, which are translated into data, data, and more data.
This data can be used in ways we would never have imagined 10 years ago. Our watches monitor our sleep time and track our daily activities; televisions understand our entertainment searches; cars, airplanes, and more show the places we go.
The number of smart devices is predicted to increase to 50 billion to 70 billion by 2020. This means the potential uses for all the information collected will be nearly endless.
The term IoT was first used in 1999 to promote radio frequency identification technology, which uses electromagnetic fields to identify and track product tags. This method of automatic identification and data capture has become very popular, so much so that it has been adopted by industries such as the automotive and textile industries.
The goal was to generate deeper insight into production to prevent theft and errors. It took 10 years to gain market popularity, and another four years to achieve widespread recognition.
Around 2014, the term Internet of Things resurfaced with widespread popularity. However, its definition within companies has not been very concrete, and therefore it has not been implemented for fear of taking risks in innovation.
From the beginning, technology has been applied in many businesses, especially in the consumer sector, in infrastructure, and in innovation.
In the consumer space , the Internet of Things has been truly disruptive. People in this segment may not be fully aware of the term, yet they are successful in executing processes that require technology.
In this day and age, wearable technology is one of the biggest draws among consumers. For example, we have the "Smart Watch," which has arrived so we can literally have everything at our fingertips. But it's not just smartwatches; there are countless electronic devices with access and authorization to various systems.
On the infrastructure side , we have manufacturing, construction, foundations, energy management, and other areas. IoT has helped efficiently monitor and control the operations of urban and rural projects, such as bridges and highways.
Automated monitoring systems have not only reduced gaps in work processes, but have also reduced operating costs.
Integration in this area has been established through devices that operate via sound, motion sensors, material identification, communicators, and processors. The greatest benefit of this implementation is real-time optimization of the supply chain.
In the corporate world , companies have developed IoT-focused apps specifically for processing and analyzing, with the goal of improving the performance of workgroups by reducing the flow of tasks for those who have to perform an activity repeatedly.
So devices, computers, markers, clocks, and other devices store information about employee activities for later analysis and improvement.
The agricultural sector has launched devices that allow users to collect information on temperature, wind speed, livestock species and number, soil properties, rainfall frequency, and ambient humidity.
These devices help farmers reduce risks and reduce crop residue. They also help insurers gather data and provide highly targeted insurance for this sector.
Many companies have adapted to implement IoT both internally and externally. Many businesses should consider incorporating it into their structure, as they can benefit from it and also grow their industry.
This type of innovation is expected to continue to expand so that businesses can deliver their products to consumers in a more detailed and focused manner.
By understanding and integrating this type of technology, you can keep your business one step ahead of your competitors.
There are millions of pieces of data floating around us. Would you like to take advantage of them and grow your business? EGOS BI can help you.
The Modern Data Stack provides flexibility and scalability for building future-proof analytics architectures, supporting AI/ML use cases and adapting to business growth without high infrastructure costs.
Automation is transforming data management by reducing manual work and ensuring data reliability. Tools like Fivetran, dbt, and Snowflake are essential for accelerating analytics.
Organizations are increasingly recognizing the limitations of traditional data architectures. Legacy systems struggle to meet modern demands, while Modern Data Stacks offer scalability, integration, and governance solutions.
Unlock the potential of your data with our expert guidance. Schedule your session today!
