LoRaWAN-Signal-Mapping/client_src/js/Worker/AIWrapper.mjs

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2.3 KiB
JavaScript
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"use strict";
import path from 'path';
import brain from 'brain.js';
import haversine from 'haversine-distance';
import {
normalise_lat,
normalise_lng,
unnormalise_lat,
unnormalise_lng,
normalise_gateway_distance,
unnormalise_gateway_distance,
normalise_rssi,
unnormalise_rssi
} from '../../../common/Normalisers.mjs';
import GetFromUrl from '../Helpers/GetFromUrl.mjs';
class AIWrapper {
constructor() {
this.setup_complete = false;
this.map_bounds = null;
this.index = null;
this.Config = null;
this.gateways = new Map();
}
async setup({ bounds, index, Config }) {
this.map_bounds = bounds;
this.index = index;
this.Config = Config;
console.log("Loading models");
// WebGL isn't available inside WebWorkers yet :-(
for(let gateway of this.index.index) {
let net = new brain.NeuralNetwork();
net.fromJSON(
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// TODO: Move this to the UI thread & do it only once?
await GetFromUrl(`${path.dirname(self.location.href)}/${path.dirname(this.Config.ai_index_file)}/${gateway.filename}`)
);
this.gateways.set(
gateway.id,
net
);
}
console.log("Model setup complete.");
this.setup_complete = true;
}
predict_row(lat) {
if(!this.setup_complete)
throw new Error("Error: Can't do predictions until the setup is complete.");
let result = [],
stats = {
rssi_min: Infinity,
rssi_max: -Infinity
};
for(let lng = this.map_bounds.west; lng < this.map_bounds.east; lng += this.Config.step.lng) {
let max_predicted_rssi = -Infinity;
for(let [gateway_id, ai] of this.gateways) {
let distance_from_gateway = haversine(
{ latitude: lat, longitude: lng },
this.gateways.get(gateway_id)
);
max_predicted_rssi = Math.max(
max_predicted_rssi,
ai.run({
latitude: normalise_lat(lat),
longitude: normalise_lng(lng),
distance: normalise_gateway_distance(
distance_from_gateway
),
})[0]
);
}
max_predicted_rssi = unnormalise_rssi(max_predicted_rssi);
if(max_predicted_rssi > stats.rssi_max)
stats.rssi_max = max_predicted_rssi;
if(max_predicted_rssi < stats.rssi_min)
stats.rssi_min = max_predicted_rssi;
result.push(max_predicted_rssi);
}
return { result, stats };
}
}
export default AIWrapper;