The Internet of Things (IoT) is emerging as the third wave in the development of the Internet. In the 1990’s 1 billion users were connected to the internet, by the 2000’s the release of Internet 2.0 and the popularity of internet capable smart phones that number grew to 3 billion, and now it is expected by 2020 the IoT will connect 28 billion devices to the internet.
According to a report published by Goldman Sachs, “The Internet of Things: Making sense of the next mega-trend” the Internet of Thing “connects devices such as everyday consumer objects and industrial equipment onto the network, enabling information gathering and management of these devices via software to increase efficiency, enable new services, or achieve other health, safety, or environmental benefits.”
The report classified the “things” as 5 key verticals for the adoption of this third wave of the Internet: Connected Wearable Devices, Connected Cars, Connected Homes, Connected Cities, and the Industrial Internet.
The infrastructure that will fully support the connection of 28 billion devices, consisting in telecommunications, sensors and software among other components will allow to use the data generated to make our lives easier (i.e. adjust the temperature of your home before you get home), use energy efficiently (i.e. turn on your washing machine when electricity usage and prices fall in the middle of the night), and help us anticipate and predict failures or problems (i.e. predict when your car is going to fail even before the check engine light turns on).
One of the main concerns about the connectivity of everything is privacy and security. The key for the IoT to develop to its full potential is to make sure the “things” are genuinely adding value instead of being merely intrusive. Goldman Sachs identified three key areas where the development of IoT will generated the most value: home automation, resources, and manufacturing.
The Industrial Internet has now invested large amounts of time and money in sensors, connectivity, micro-controllers and micro-processors, and the amount of data generated is often times large and unintuitive. The missing piece of that puzzle is software that combines all that information and analyzes it to transform it into actionable outputs.
Many predictive analytics companies are trying to solve a technology problem. How will you manage all that data? Should we use Hadoop or No-SQL? What are the issues of the IT department regarding the data they are collecting? I have a huge amount of data that the company is not using, is there valuable information that isn’t being leveraged? But they are not solving the main issue: what problems are you having in your manufacturing facilities that are slowing down your production rates? How can the existing data help you to reach and surpass the production goals reducing downtimes and inefficiencies?
If the operational problems are not being solved, the future of the IoT will not be bright.