

What Is the Internet of Things?
The Internet of Things (IoT) refers to the network of smart devices that are connected to the Internet and use software and sensors to enable the sending and receiving of data. Enterprises can use this data to enhance business processes, reduce manual work (and data capturing), and increase overall efficiency. IoT is fueled by the creation of “denser, faster, cheaper” computer chips and faster Internet for better connectivity in every environment.
IoT has empowered organizations to make huge strides toward being more data-driven and automating business processes that depend on data.
Enterprises collect this data to:
- Prevent problems and offer new value-added services
- Enable business process automation
- Enhance device connectivity and asset management
- Manage KPIs to improve operational performance
- Optimize decision-making with data science
Why Is the Internet of Things So Important?
IoT is important for enterprises because it provides a constant stream of concrete data from sources that were remote, inaccessible, or disconnected from core operations. This data can be used to paint a picture of what’s happening in your field operations in real-time.
Enterprises can process this data using big data systems, machine learning frameworks, and analytics software to gain insights for decision-makers. For example, enterprises use IoT data to support predictive maintenance use cases as well as proactive monitoring of expensive industrial equipment. Plus, IoT enables remote control and management of these devices.
Improve product performance
While industrial and field operations use cases are common, companies also use IoT to capture data directly from their own products to gain insights that ultimately help make their products better.
Many electronics manufacturers are adding sensors to their products so they can get feedback and data about their devices’ performance. The chips that monitor the sensors, of course, have to be durable and designed to withstand demanding environmental conditions.
Get notifications & analysis in real-time
IoT applications commonly use machine learning anomaly detection techniques to analyze incoming data, which can alert operators of device failures and conditions that may lead to downstream issues.
For example, your smart refrigerator can send an alert about humidity that has risen above an acceptable threshold. Some smart devices can trigger automated fixes if a core capability is malfunctioning.
Optimize the supply chain
Supply chain optimization makes the best use of IoT technology by improving efficiency and performance, thus increasing customer satisfaction. IoT-enabled enterprises can continually improve the supply chain by collecting data and gaining insights into delays, breakdowns, and bottlenecks.
There are a few key ways that IoT can help make the supply chain more efficient:
Real-time alerts
Real-time alerts about location and environmental data combined with big data, machine learning, and data analytic tools help enterprises to:
- Anticipate problems
- Deliver new value products
- Improve performance and productivity
- Optimize processes
- Gain visibility of the supply chain processes
- Improve the decision-making process
Automatic data gathering
Automatic data gathering and data analytics tools allow for faster compliance and performance checks, all while analyzing and optimizing the chain as a whole in the background.
Tracking assets
Tracking goods prevents accidents, losing assets, and poor productivity. IoT helps enterprises trace each step and figure out all potentially vulnerable and hazard points for damage monitoring and prevention. For example, IoT collects the location and environmental data, and gives users visibility and better control of hazardous materials, thus minimizing risk for employees.
Monitor employee safety
Discrete use of wearables and biometric sensors with consenting employees can help prevent accidents in the workplace.
In industrial settings, sensors can be used to detect when employees display signs of extreme fatigue and recommend when they should not be operating heavy machinery or be attached to forklifts to prevent collisions. Data can be analyzed to detect patterns, such as danger zones in warehouses, or identify causality between employee fatigue and accidents.
IoT can also enable speedier responses to accidents when they inevitably occur. For example, on a construction site, sensors can detect a high-impact collision from a fall or a vehicle crash and elicit an emergency response.
Monitor machines & product quality
With IoT monitoring, you can analyze data and check performance. IoT real-time sensors identify any device quality defects that occur. When the output of a machine does not meet quality standards, IoT data can be assessed to find precursors that may reveal triggering events.
Improve asset tracking
Using tech for asset tracking is nothing new, but IoT sensors track assets and enable users to collect location data and environmental data.
Sensors can enhance tracking and geo-fencing of high-value assets, such as expensive heavy machinery and high-tech equipment — like VR systems. This can help prevent theft, damage, poor productivity due to misplaced equipment, and total loss.
Using IoT, enterprises can gain full visibility across the supply chain.
Improve fleet efficiency
Managing a fleet of vehicles can be challenging, but IoT comes to the rescue. In real-time, companies can see which vehicles are most productive and fuel efficient and even perform routine safety checks while vehicles are in operation.
Changes can be made to routes, in real-time, so deadlines are met. Even drivers can be monitored through IoT to make sure they are following the strict government safety restrictions of time on the road and distance covered each day.
Improve energy efficiency
Monitoring energy and processing data allow enterprises to predict energy demand and optimize future consumption. Machine sensors can identify unnecessary energy drain and automatically power down devices.
Want to Analyze IoT Collected Data & Gain Insights?
IoT devices combined with data science tools help analytic teams and stakeholders improve efficiency, deliver data analytics insights, and improve decision-making processes.
A powerful tool like RapidMiner helps enterprises in each step of the data science process, including data prep, model deployment, and model operations. About 400,000 data scientists, business analysts, and engineers are using the RapidMiner platform to increase revenue, minimize costs, and reduce risks.
More than 40,000+ global organizations in every industry who use the RapidMiner data science platform to drive revenue, reduce costs, and avoid risk.
Want to learn more about specific use cases for data science at your organization? Request a demo with RapidMiner today.