Local weather forecasts, crossed with the yield curve measured on the unit itself, give expected output three days out.
Output expected to fall 30 %→Reserve topped up before the dip
On an isolated site, everything is decided after delivery. Amanow monitors its installations remotely, intervenes before the breakdown, and reports on what is actually produced.
Every unit is instrumented and transmits its readings over the mobile network, with local memory in case of an outage. No manual reading is asked of the site staff.
Data nobody acts on is a cost, not an asset. Four readings, four decisions they trigger.
Local weather forecasts, crossed with the yield curve measured on the unit itself, give expected output three days out.
The alert does not trigger on a low tank level, but on remaining autonomy judged against observed consumption and expected production.
Yield drift signals a clogged filter, a refrigerant leak or a weakening compressor, often weeks before the stoppage. On scattered sites, every avoided journey is a direct saving.
A local operator is trained on every site, with remote assistance in Darija, French and English, reachable from a basic phone for first-level diagnosis. Our teams travel for what genuinely requires it.
Our installations are financed by public budgets and by funders who must account for the use of their money. The report that lets them do it is produced by the system, not written after the fact.
We separate what is operational from what will come with the fleet. Readings and alert thresholds work from the first installation. Forecast and anomaly-detection models are calibrated site by site, as history builds up: they are only as good as the data behind them, and that data does not exist yet.
The proof of concept under way at a public university in Morocco is instrumented for exactly this purpose.
Ask us what we monitor, how often, and who receives the report.
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