Data Analytics in IoT Industries
Data Analytics กับ IoT Industries
Today, organizations are becoming increasingly aware of the importance of using data and are moving towards becoming data-driven organizations. Do you know how much data will be generated in the future and how we can leverage that data?
According to Statista’s data, the volume of data consumed worldwide from 2010-2025 is projected to increase significantly, reaching up to 149 zettabytes by 2024. This substantial increase emphasizes the importance of using data, particularly in industries related to IoT (Internet of Things).
What is IoT?
IoT refers to the automatic connection of various devices and electronic equipment to the Internet, allowing for easy control and communication with other devices. Examples of IoT devices commonly seen today include smart devices like smartwatches, smart homes, and running shoes that collect and analyze running data.
Benefits of IoT
Since data received from IoT devices can be monitored, collected, and analyzed, IoT facilitates the rapid flow of data. However, it requires the use of big data for real-time data storage.
How Data Analytics Can Be Applied to IoT
- Discovering hidden patterns in data.
- Finding new insights in data.
- Predicting data trends and future events.
- Identifying relationships between different sets of data.
Examples of Applications in Various Industries
- Transportation: Managing traffic loads efficiently, such as scheduling public transportation or controlling traffic lights to reduce congestion.
- Retail: Preventing out-of-stock items in supermarkets by providing advance notifications to restock products.
- Agriculture: Ensuring crops receive the right amount of water and planning agricultural production accordingly.
- Healthcare: Using data to monitor patients’ conditions and predict health risks.
- Manufacturing: Avoiding factory accidents by predicting machine failures and identifying potential issues.
Preparing for the Future As organizations transition to becoming data-driven, they need to prepare for the data generated in the future, especially the large volumes of IoT data. So, the question is, is your organization ready to deal with this massive influx of data, and to what extent?
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