Knowing where to start with using AI to solve real value-adding business problems can be challenging. The Ekkono Software Development Kit is a generalized edge machine learning tool, used for making connected things smart. Enjoy a selection of smart use cases that our SDK enables.
We like to illustrate product smartness using a cognitive staircase, where the steps represent the complexity level of each use case. As every step benefits from the one below, this highlights the importance of getting the basics right when enhancing your product portfolio with machine learning capabilities.
Virtual Sensor [Current State]
Physical sensors could be expensive, prone to fail or to drift. With the Ekkono SDK, you can create a virtual sensor based on related physical sensors. The virtual sensor can then replace a physical sensor, provide support on sensor failure or act as a reference when monitoring drift and anomalies. A virtual sensor “measures” signals […]
Health Monitoring [Current State)
Health monitoring provides insights about system health beyond raw sensor values, and helps you prevent severe failures and unplanned production stops by exposing the true health of your machine. When using incremental learning, the need of historic data is replaced by the power of real-time data. Edge OpportunitiesWith Ekkono’s edge machine learning SDK it is […]
Predictive Alarming [Predictive]
Predictive alarming lets you apply alarm levels on future sensor values, enabling the possibility to act in advance. Alarms on predicted values gives valuable input to operation teams, preventing potential problems from happening, thereby increasing uptime and prolonging machinery life. Edge OpportunitiesEkkono’s SDK enables predictive alarming by letting a machine learning model predict future sensor […]
Predictive Maintenance [Predictive]
Predictive maintenance minimizes downtime and optimizes periodic maintenance by moving from scheduled to smart maintenance planning, letting the health state of the machine, rather than a periodic time interval, decide when to carry out maintenance. Edge OpportunitiesTraditional predictive maintenance relies on models trained on significant amounts of data including both positive and negative data points […]
Decision Support [Prescriptive]
Before making changes to a device or process, you want to know the impact of that change. A predictive model, that simulates different scenarios, can give you that information. By capturing information about the impact of different machine settings and configurations, a decision support system can provide recommendations to the user, enhancing the user experience […]
Auto-tuning releases the full capacity of machine learning systems, enabling smart self-configuration systems, increasing equipment utilization, improving energy efficiency and lowering environmental footprint. Edge OpportunitiesEkkono’s SDK enables autonomous performance optimization, on the edge in real-time. Use a machine learning model to explain complex behavior of a machinery and add an optimizer to find parameters for […]
Predictive Control [Cognitive]
Predictive control is a powerful alternative to traditional control, especially when handling complex systems with unknown dynamics and parameters. Predictive control can make use of multivariable input, infer the underlying model through observations and use predictions of future state in a control loop.Predictive control can in many systems be self-configuring, saving time and cost. Edge […]