Energy management and optimization would not have come easy, if there was no active monitoring, signaling and regulating structure in place. One of the fundamentals in the overall objectives of our product and service framework, is to put the intents and preferences of the various users, to consideration. Hence, there is the need to have a system that understands the specific energy requirements of the users per time, such that it favors them- both in cost, as well as in energy resource management.

Robotina’s cognitive optimization system brings all that is needed to achieve these objectives. It is an accompanying function feature for any of our delivered working product, with input allowances that ensures its effective purpose continuity.

How the system works

The cognitive optimization system (COS) works based on a series of set rules, and basic outlined instructions- which is the underlying model for carrying out every of its assigned tasks. This means, the system has been programmed to function in such a way that aligns the operation of installed IoT devices, with the user’s laid out energy use plans. Robotina’s COS is well detailed and responsive, to work well with a network of all the connected energy utilizing appliances in a home or building structure, no matter how seemingly complex the electrical architecture of it.
In order to keep up with the expected energy use dynamics of the utilizing household, the optimization system learns and understands the changing energy use preferences of the users, and communicates same to the IoT devices for implementation; this, it does in the form of assigned new rules and/or optimized application software.
Basically, this control sector of the platform has been imputed with an innate ability through machine learning, to correct and modify function algorithms, models, and rules, such that they conform to the current peculiarities of the users. For instance, in the event that the energy pricing tariff system of the user changes, the cognitive optimization system is able to make the right call with our overall platform, to fashion out a new or modified strategy which is tested for precision before being communicated to the implementing IoT things. This means, the system is always connecting and keeping in touch with the platform to either collaborate with it for the design of a new work strategy, or to keep it updated with the energy use occurrences, or both simultaneously.

Importance of the cognitive optimization system to end users

From the cognitive optimization system’s work descriptions, there are a number of benefits that its activities is able to bring directly for the users. Some of these advantages includes the following:
• Helping users reduce their energy and maintenance costs, by as much as up to 30% in estimates.
• Plays an important role in fault prediction and detection on energy using appliances, thus saving the user from extra costs on damages, and excess repairs.
• Cognitive optimization system updates the user’s installed and running energy management and optimization features, with current effective use methods and incentives from our platform.

In conclusion

Although the Robotina company still has other component structures that meets contemporary technological standards, the cognitive optimization system is an impressive lot. This is why we can rely on it to carry out even the most tasking operations that could be.