Does it make sense?
Imagine your reaction when seeing the following on a rainy day:
- A person watering his garden with a hose,
- A working sprinkler system.
Both scenarios do not really make sense, don’t they? After all, both result with a waste of water.
A rational person would not water his garden when it rains or would simply stop watering it as soon as it starts to rain. However, the sprinkler system might be on because it was automatically set to start working on a certain part of the day, or because someone forgot to turn it off just before the wet season. The system would keep on running until it reaches the end of its cycle, or until someone or some machine with a pre-set timer will turn it off.
If we could “teach” the sprinkler system to stop working when it’s raining, that would be really cool. That’s the essence of Artificial Intelligence (AI): To make a machine “think on its own,” respond to changing conditions, and take appropriate actions.
Galooli’s unique AI algorithm
While Galooli doesn’t deal with water sprinklers (at least not yet) it has a lot to offerwhen it comes to AI, especially in the context of tracking and monitoring of connected assets and power sites.
Off grid telecom sites, namely sites which are not connected to power lines, might rely on three different power sources:
- Rechargeable batteries
- Generators (which charge the batteries and back them up)
- Solar panels (which are also used to charge the batteries)
Using these three power sources at the same time is equivalent to watering the garden when it’s raining. More specifically, operating a generator when free energy from the sun is flowing through solar panels, makes no sense whatsoever. It would also be unwise to enable solar panels to overcharge batteries.
In other words, it is better to use these power sources in an orchestrated and balanced way, that would make the best out of each one of them separately, and all of them together, without consuming unnecessary energy.
Galooli knows how to do it! Our unique AI algorithm continuously “teaches” itself how to ultimately react to changing conditions and circumstances, such as the weather, workload, and battery status. The following are some of the questions the algorithm keeps considering:
- Weather – How efficient will the solar panels be?
- Workload – how intensive should the generators work, if at all, during different times of the day and night?
- Batteries – is it necessary to fully charge batteries at all times?
Galooli’s AI algorithm is already in use on telecom sites globally.
It increases sites’ efficiency and saves our customers millions of dollars.