IoT Analytics Platforms Resources

EMnify only charges for the data consumption of active SIMs. SIMs can be suspended and activated any time. The invoice will be billed at the end of the month.

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TrendMiner is used for advanced analytics in process manufacturing industries. Its primary functions and applications include: Real-Time Monitoring: It allows for the continuous observation of batch, grade, and continuous processes in real-time, enabling users to quickly identify and address production issues. Predictive Insights: By leveraging historical data and machine learning algorithms, TrendMiner provides predictive insights into future process behaviors and outcomes. This feature helps in proactive decision-making and process optimization. User-Friendly Analytics: Designed with an intuitive web-based interface, TrendMiner is accessible to users without in-depth data science expertise, making it easier for various team members to utilize the platform. Flexible Deployment: TrendMiner offers various deployment options such as Software as a Service (SaaS), on-premises, or private cloud. This flexibility ensures that it can be integrated seamlessly into different IT environments. Quick Return on Investment (ROI): The platform is known for providing immediate value post-deployment, offering actionable insights that can lead to efficiency improvements and cost savings. Industry Agnostic: While it is particularly beneficial for process manufacturing, TrendMiner is versatile and suitable for various sectors, including manufacturing, chemicals, oil and gas, and pharmaceuticals. Scalability and Future-Proofing: TrendMiner can handle large volumes of data and integrates well with existing systems, ensuring that it remains relevant and effective as an organization grows and evolves. Data-Driven Decision Making: It enables companies to make more informed decisions based on data analytics, improving overall process efficiency, product quality, and operational safety.

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ExoSense is used by organizations to monitor and manage equipment and machines. By leveraging ExoSense they are able to get realtime access to how the asset is performing, use transform logic and rules to alert on status changes, manage conditions, and look at historical data - including leveraging ML / AI and Data Science tools. Product companies and OEMs will often use ExoSense to provide services to their customers, either with direct maintenance and/or by providing recommendations on operating and maintaining the asset. Businesses, manufacturers, and utilities are able to leverage ExoSense to improve performance, find ways to reduce costs, optimize teams and maintenance, and have better insight into how equipment is being operated. Some example of assets and processes connected to ExoSense include: - Pumps, Rotating Equipment, Valves, Hydraulic Power Units (HPUs) - Factory Machines - Construction, Commercial, and Utility Vehicles - Large Power Generation Diesel Engines - Agricultural Environmental Sensors - Electric Battery, Charging Equipment, Alternative Energy Generation - Manufacturing Processes - Sensors (Wired/Wireless): Tank level, Flow, Temperature, Pressure, Air Quality .etc

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