Internet of Things (IoT) analytics is a data analysis tool that evaluates the wide range of data collected from IoT devices. IoT analytics assesses large volumes of data to produce valuable information that can benefit businesses and other organizations.
IoT analytics is often connected to Industrial IoT (IIoT). In industrial applications, data is collected from multiple sources, such as manufacturing equipment, climate monitoring systems, and delivery vehicles. IoT analytics is then used to optimize data management systems and improve operations.
IoT and big data analytics have several similarities. The primary difference between the two is how each obtains the data they analyze. Big data uses large amounts of data already recorded for future analysis, while IoT data is collected and assessed in real time.
How Does IoT Analytics Work?
IoT analytics helps companies conveniently monitor enormous amounts of data from multiple devices without requiring specific infrastructure. Moreover, IoT's scalability allows organizations to adjust computing power and data storage to adapt to changing business needs.
Data collection is the first step in IoT analytics. Data is gathered from different sources and formats before being processed through various external sources. Once ready, the information is stored for real-time analysis, producing actionable insights that can be used to make informed predictions.
Organizations can also utilize the information received to innovate new systems and applications to improve business processes.
Common IoT Analytics Devices
- Connected Devices
Connected devices, usually digital assistants, are among today's most common IoT platforms. For instance, Alexa, Siri, and Google excel at storing user information and analyzing it to suggest music, order food, set appointments, and assist in other activities. These devices are regularly updated to improve functionality and operability.
- Healthcare
There is a wide range of IoT analytics platforms in the healthcare industry. There are analytics solutions that can record heart rates and blood pressure to help monitor irregularities and address them promptly. Some hearing aids are enhanced with Bluetooth technology for increased convenience and personalization.
- Smart Home
The digital transformation has led to the creation of smart homes, where users can easily manage several appliances and house functions from a smartphone or tablet. Smart security systems can also be installed so homeowners can remotely monitor their residences and prevent breaches.
- Wearables
Devices like Fitbit and other smartwatches have advanced beyond just tracking steps. Users can now connect with their friends to compare progress and communicate online. The data collected is used by fitness companies to create personalized plans for users, like exercise regimens, dieting, and goal setting. Moreover, the latest models of smartwatches can monitor heart rates and rhythms to help identify possible heart issues in users.
Top Business Applications of IoT Analytics
- Inventory Management
Companies can use connected machines to monitor and manage their inventories remotely. For instance, machine learning capabilities can help vending machines process inventory data and request restocking when stocks reach a specific count.
- Predictive Maintenance
Many types of infrastructure require regular maintenance to function correctly. Businesses can rely on IoT analysis to create quality predictive maintenance models tailored to particular needs. For example, IoT analytics can help transport vehicles with heating or cooling systems determine when an overhaul is necessary to ensure the cargo remains safe during transit.
- Smart Agriculture
Farmers can leverage IoT analytics to gain powerful insights regarding crop health, harvest patterns, weather trends, and inefficiencies in their production process so they can take corrective actions quickly.
The Benefits and Challenges of IoT Analytics
IoT analytics brings many benefits, such as actionable intelligence and invaluable insights. These can result in the following:
- Better control and increased visibility leading to quicker and more informed decision-making
- Improved scaling and flexibility regarding business needs, allowing for expansion opportunities in additional markets
- Less operational costs due to automation technologies and improved resource management
- New revenue streams resulting from the clearing of operational challenges
- Quicker solutions from accurate pinpointing of problems
- Enhanced customer experience due to improved products and operations
Despite these benefits, IoT analytics does not come without its share of difficulties. Some of the significant challenges of IoT analytics include the following:
- Static data issues leading to diagnostic and predictive errors
- Speed and storage imbalance due to scaling and time series problems
- Hiring skilled professionals such as developers, database specialists, and data scientists to manage IoT data processes
A Final Word on IoT Analytics
As more people rely on Internet of Things (IoT) devices, a growing abundance of data becomes available to organizations. This data is collected from different sources, from personal devices and home automation systems to automobiles and industrial technologies.
Since data is constantly being produced and gathered, organizations can gain valuable insights and information through IoT analytics. By leveraging the collected device data, organizations can better understand their customers, operations, and the ever-changing market dynamics, helping them make more informed business decisions.
