LoRaWAN-Signal-Mapping/server/train-ai/AITrainer.mjs

"use strict";

import tf from '@tensorflow/tfjs-node-gpu';

class AITrainer {
	constructor({ settings, GatewayRepo, DatasetFetcher }) {
		this.settings = settings;
		this.dataset_fetcher = DatasetFetcher;
		this.repo_gateway = GatewayRepo;
		this.model = this.generate_model();
	}
	
	generate_model() {
		let model = tf.sequential();
		model.add(tf.layers.dense({
			units: 256, // 256 nodes
			activation: "sigmoid", // Sigmoid activation function
			inputShape: [3], // 2 inputs - lat and long
		}))
		model.add(tf.layers.dense({
			units: 1, // 1 output value - RSSI
			activation: "sigmoid" // The example code uses softmax, but this is generally best used for classification tasks
		}));
		
		model.compile({
			optimizer: tf.train.adam(),
			loss: "absoluteDifference",
			metrics: [ "accuracy", "meanSquaredError" ]
		});
		
		return model;
	}
	
	async train() {
		for(let gateway of this.repo_gateway.iterate()) {
			let dataset = this.dataset_fetcher.fetch(gateway.id);
			await this.train_dataset(dataset);
		}
	}
	
	async train_dataset(dataset) {
		// TODO: Fill this in
	}
}

export default AITrainer;