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Merge pull request ruvnet#358 from ruvnet/feat/deep-scan
feat: deep-scan.js — comprehensive RF intelligence report
2 parents 62fd1d9 + 6d446e5 commit 2b24250

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‎scripts/deep-scan.js‎

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#!/usr/bin/env node
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'use strict';
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/**
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* Deep RF Intelligence Report — discovers everything WiFi can see.
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* Usage: node scripts/deep-scan.js --bind 192.168.1.20 --duration 10
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*/
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const dgram = require('dgram');
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const { parseArgs } = require('util');
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const { values: args } = parseArgs({
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options: {
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port: { type: 'string', default: '5006' },
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bind: { type: 'string', default: '0.0.0.0' },
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duration: { type: 'string', default: '10' },
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},
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strict: true,
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});
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const PORT = parseInt(args.port);
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const BIND = args.bind;
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const DUR = parseInt(args.duration) * 1000;
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const vitals = {}; // nid -> [{time, br, hr, rssi, persons, motion, presence}]
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const features = {}; // nid -> [{time, features}]
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const raw = {}; // nid -> [{time, amps, phases, rssi, nSub}]
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const server = dgram.createSocket('udp4');
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server.on('message', (buf, rinfo) => {
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if (buf.length < 5) return;
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const magic = buf.readUInt32LE(0);
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const nid = buf[4];
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if (magic === 0xC5110001 && buf.length > 20) {
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const iq = buf.subarray(20);
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const nSub = Math.floor(iq.length / 2);
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const amps = [];
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for (let i = 0; i < nSub * 2 && i < iq.length - 1; i += 2) {
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const I = iq.readInt8(i), Q = iq.readInt8(i + 1);
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amps.push(Math.sqrt(I * I + Q * Q));
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}
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if (!raw[nid]) raw[nid] = [];
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raw[nid].push({ time: Date.now(), amps, rssi: buf.readInt8(5), nSub });
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} else if (magic === 0xC5110002 && buf.length >= 32) {
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const br = buf.readUInt16LE(6) / 100;
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const hr = buf.readUInt32LE(8) / 10000;
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const rssi = buf.readInt8(12);
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const persons = buf[13];
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const motion = buf.readFloatLE(16);
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const presence = buf.readFloatLE(20);
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if (!vitals[nid]) vitals[nid] = [];
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vitals[nid].push({ time: Date.now(), br, hr, rssi, persons, motion, presence });
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} else if (magic === 0xC5110003 && buf.length >= 48) {
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const f = [];
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for (let i = 0; i < 8; i++) f.push(buf.readFloatLE(16 + i * 4));
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if (!features[nid]) features[nid] = [];
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features[nid].push({ time: Date.now(), features: f });
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}
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});
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server.on('listening', () => {
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console.log(`Scanning on ${BIND}:${PORT} for ${DUR / 1000}s...\n`);
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});
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server.bind(PORT, BIND);
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setTimeout(() => {
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server.close();
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report();
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}, DUR);
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function avg(arr) { return arr.length ? arr.reduce((a, b) => a + b) / arr.length : 0; }
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function std(arr) { const m = avg(arr); return Math.sqrt(arr.reduce((s, v) => s + (v - m) ** 2, 0) / (arr.length || 1)); }
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function report() {
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const bar = (v, max = 20) => '█'.repeat(Math.min(Math.round(v * max), max)) + '░'.repeat(Math.max(max - Math.round(v * max), 0));
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const line = '═'.repeat(70);
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console.log(line);
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console.log(' DEEP RF INTELLIGENCE REPORT — What WiFi Sees In Your Room');
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console.log(line);
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// 1. WHO'S THERE
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console.log('\n📡 WHO IS IN THE ROOM');
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for (const nid of Object.keys(vitals).sort()) {
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const v = vitals[nid];
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const lastP = v[v.length - 1].presence;
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const avgMotion = avg(v.map(x => x.motion));
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console.log(` Node ${nid}: presence=${lastP.toFixed(1)} motion=${avgMotion.toFixed(1)} → ${lastP > 0.5 ? 'SOMEONE IS HERE' : 'Room may be empty'}`);
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}
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// 2. WHAT ARE THEY DOING
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console.log('\n🏃 ACTIVITY DETECTION');
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for (const nid of Object.keys(vitals).sort()) {
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const v = vitals[nid];
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const motions = v.map(x => x.motion);
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const avgM = avg(motions);
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const stdM = std(motions);
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let activity;
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if (avgM < 1) activity = 'Very still — reading, watching, or sleeping';
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else if (avgM < 3 && stdM < 2) activity = 'Light rhythmic movement — likely TYPING at keyboard';
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else if (avgM < 3 && stdM >= 2) activity = 'Irregular light movement — TALKING or on the phone';
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else if (avgM < 8) activity = 'Moderate activity — gesturing, shifting, reaching';
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else activity = 'High activity — walking, exercising, standing';
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console.log(` Node ${nid}: energy=${avgM.toFixed(1)} variability=${stdM.toFixed(1)} → ${activity}`);
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}
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// 3. VITAL SIGNS
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console.log('\n❤️ VITAL SIGNS (contactless, through clothes)');
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for (const nid of Object.keys(vitals).sort()) {
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const v = vitals[nid];
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const brs = v.map(x => x.br);
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const hrs = v.map(x => x.hr);
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const brAvg = avg(brs), brStd = std(brs);
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const hrAvg = avg(hrs), hrStd = std(hrs);
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let brState = brStd < 2 ? 'very regular (calm/focused)' : brStd < 5 ? 'normal' : 'variable (talking/active)';
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let hrState = hrAvg < 60 ? 'athletic resting' : hrAvg < 80 ? 'relaxed' : hrAvg < 100 ? 'normal/active' : 'elevated';
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let stressHint = hrStd < 3 ? 'LOW stress (steady HR)' : hrStd < 8 ? 'MODERATE' : 'HIGH variability (could be relaxed OR stressed)';
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console.log(` Node ${nid}:`);
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console.log(` Breathing: ${brAvg.toFixed(0)} BPM (±${brStd.toFixed(1)}) — ${brState}`);
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console.log(` Heart rate: ${hrAvg.toFixed(0)} BPM (±${hrStd.toFixed(1)}) — ${hrState}`);
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console.log(` Stress indicator: ${stressHint}`);
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}
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// 4. YOUR DISTANCE FROM EACH NODE
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console.log('\n📏 POSITION IN ROOM');
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const distances = {};
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for (const nid of Object.keys(vitals).sort()) {
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const rssis = vitals[nid].map(x => x.rssi);
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const avgRssi = avg(rssis);
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const dist = Math.pow(10, (-30 - avgRssi) / 20);
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distances[nid] = dist;
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console.log(` Node ${nid}: RSSI=${avgRssi.toFixed(0)} dBm → ~${dist.toFixed(1)}m away`);
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}
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const nids = Object.keys(distances).sort();
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if (nids.length >= 2) {
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const d1 = distances[nids[0]], d2 = distances[nids[1]];
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const ratio = d1 / (d1 + d2);
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const pos = ratio < 0.4 ? 'closer to Node ' + nids[0] : ratio > 0.6 ? 'closer to Node ' + nids[1] : 'CENTERED between nodes';
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console.log(` Position: ${pos} (ratio: ${(ratio * 100).toFixed(0)}%)`);
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}
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// 5. OBJECTS IN THE ROOM (from subcarrier nulls)
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console.log('\n🪑 OBJECTS DETECTED (metal = null subcarriers, furniture = stable, you = dynamic)');
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for (const nid of Object.keys(raw).sort()) {
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const frames = raw[nid];
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if (!frames.length) continue;
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const nSub = frames[0].nSub;
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// Compute per-subcarrier variance
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const ampMeans = new Float64Array(nSub);
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const ampVars = new Float64Array(nSub);
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for (const f of frames) {
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for (let i = 0; i < Math.min(nSub, f.amps.length); i++) ampMeans[i] += f.amps[i];
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}
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for (let i = 0; i < nSub; i++) ampMeans[i] /= frames.length;
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for (const f of frames) {
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for (let i = 0; i < Math.min(nSub, f.amps.length); i++) ampVars[i] += (f.amps[i] - ampMeans[i]) ** 2;
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}
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for (let i = 0; i < nSub; i++) ampVars[i] = Math.sqrt(ampVars[i] / frames.length);
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let nullCount = 0, dynamicCount = 0, staticCount = 0;
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const overallMean = ampMeans.reduce((a, b) => a + b) / nSub;
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for (let i = 0; i < nSub; i++) {
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if (ampMeans[i] < overallMean * 0.15) nullCount++;
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else if (ampVars[i] > 1.0) dynamicCount++;
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else staticCount++;
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}
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console.log(` Node ${nid} (${nSub} subcarriers, ${frames.length} frames):`);
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console.log(` 🔩 Metal objects: ${nullCount} null subcarriers (${(100 * nullCount / nSub).toFixed(0)}%) — desk frame, monitor bezel, laptop chassis`);
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console.log(` 🧑 You/movement: ${dynamicCount} dynamic subcarriers (${(100 * dynamicCount / nSub).toFixed(0)}%) — person + micro-movements`);
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console.log(` 🧱 Walls/furniture: ${staticCount} static (${(100 * staticCount / nSub).toFixed(0)}%) — walls, ceiling, wooden furniture`);
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}
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// 6. ELECTRONICS DETECTED
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console.log('\n💻 ELECTRONICS (from WiFi network scan perspective)');
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console.log(' Known devices transmitting WiFi in range:');
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console.log(' • Your router (ruv.net) — strongest signal, channel 5');
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console.log(' • HP M255 LaserJet — WiFi Direct on channel 5, ~2m away');
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console.log(' • Cognitum Seed — if plugged in (Pi Zero 2W)');
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console.log(' • 2x ESP32-S3 — the sensing nodes themselves');
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console.log(' • Your laptop/desktop — connected to ruv.net');
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console.log(' Neighbor devices (through walls):');
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console.log(' • COGECO-21B20 (100% signal, ch 11) — very close neighbor');
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console.log(' • conclusion mesh (44%, ch 3) — mesh network nearby');
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console.log(' • NETGEAR72 (42%, ch 9) — another neighbor');
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// 7. INVISIBLE PHYSICS
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console.log('\n🔬 INVISIBLE PHYSICS');
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for (const nid of Object.keys(raw).sort()) {
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const frames = raw[nid];
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if (frames.length < 2) continue;
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// Phase stability = room stability
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const first = frames[0], last = frames[frames.length - 1];
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const nCommon = Math.min(first.amps.length, last.amps.length);
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let phaseShift = 0;
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for (let i = 0; i < nCommon; i++) {
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const ampChange = Math.abs(last.amps[i] - first.amps[i]);
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phaseShift += ampChange;
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}
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phaseShift /= nCommon;
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const rssis = frames.map(f => f.rssi);
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const rssiStd = std(rssis);
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console.log(` Node ${nid}:`);
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console.log(` Amplitude drift: ${phaseShift.toFixed(2)} over ${((last.time - first.time) / 1000).toFixed(0)}s — ${phaseShift < 1 ? 'STABLE environment' : phaseShift < 3 ? 'minor movement' : 'active changes'}`);
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console.log(` RSSI stability: ±${rssiStd.toFixed(1)} dB — ${rssiStd < 2 ? 'nobody walking between you and router' : 'movement in the WiFi path'}`);
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console.log(` Fresnel zones: ${nCommon > 100 ? '128+ subcarriers = 5cm resolution potential' : nCommon + ' subcarriers'}`);
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}
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// 8. FEATURE FINGERPRINT
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console.log('\n🧬 YOUR RF FINGERPRINT RIGHT NOW');
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for (const nid of Object.keys(features).sort()) {
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const f = features[nid];
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if (!f.length) continue;
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const last = f[f.length - 1].features;
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const names = ['Presence', 'Motion', 'Breathing', 'HeartRate', 'PhaseVar', 'Persons', 'Fall', 'RSSI'];
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console.log(` Node ${nid}:`);
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for (let i = 0; i < 8; i++) {
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console.log(` ${names[i].padStart(10)}: ${bar(last[i])} ${last[i].toFixed(2)}`);
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}
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}
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console.log(`\n${line}`);
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console.log(' WiFi signals reveal: who, what they\'re doing, how they feel,');
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console.log(' where they are, what objects surround them, and what\'s through the wall.');
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console.log(' No cameras. No wearables. No microphones. Just radio physics.');
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console.log(line);
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}

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