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Sensor Data Analytics

"Implementing Spontaneity in Business Decision-Making"

To collect and evaluate data from sensor-equipped devices used in a variety of industries, including manufacturing, healthcare, retail, oil and gas, automotive, energy, transportation, logistics, agriculture, smart cities, and more, sensor data analytics is required. Ad hoc and real-time data analytics are made possible by these technologies, which can be used to maximize asset use, monitor environmental conditions, and facilitate preventive maintenance. Rootfacts provides advanced analytics for improved operations with actionable Sensor Data analytics which makes use of AI/ML-powered capabilities to forecast extremely accurate outcomes, identify important occurrences, reduce long-term risks, and automate operations with intelligent commands.

Sensor Data Analytics: What is it?

A technology called sensor data analytics can gather and examine sensor information related to your company. The components of a sensor data analytics system are three: 

    Sensors that gather information

    Connectivity of some kind to enable the cloud to receive the sensor readings 

    An analytical instrument for data organization and interpretation

     Many sensors in contemporary settings are already internet-connected, allowing them to send data for cloud analysis. The Internet of Things, or IoT analysis, is dependent on networked devices that can exchange data, frequently instantly.

Network and Cloud

The specifics of your sensors’ information relay depend on several variables, including power consumption, internet speed, and device capabilities. Your sensors may occasionally be able to transmit data in real-time to the cloud. In other scenarios, sensors transmit data in batches. Sensors use the internet to transmit data in each of those scenarios. We help with analytical tools that format, store, and analyze the data once it reaches the cloud, enabling you to make sense of it.

It’s nearly impossible to go through raw data on your own and make inferences from it. Similarly, integrating unformatted data with other types of data might be challenging. You must make sure that both data sets have the same format, for example, if you want to investigate whether the temperature in your warehouse affects the quality of the air. An essential component of any data analytics system is software for organizing and formatting data. Moreover, it’s important to have an expert team to back you up with the operations associated with handling dynamic data sets.

Applications of sensor data analysis for businesses

Sensor data analysis can be used in almost any industry to increase efficiency and optimize company procedures. For instance, farmers utilize sensor data to keep an eye on the amount of moisture in the soil and search for harmful bugs. 

Sensor data is used by factory owners to track the condition of their machinery and identify when repairs are necessary. Businesses across all industries can employ sensor data analysis to expedite calculation times and make well-informed judgments.

Efficient infrastructure management

Sensors can monitor the resilience of infrastructure and identify specific areas in need of upgrading. When applied appropriately, sensor data analytics may determine a building’s weak points, monitor water quality and consumption, and evaluate interior air quality. Through their excellent tuning, modern sensors can detect possible issues early on, giving you plenty of time to fix them.

 

Why Rootfacts?

If you are worried about how to extract valuable insights from sensor data and improve operational efficiency? we are always ready to help you. Rootfacts has an excellent team of skilled professionals in the respective domain to guide you in the right direction