Breaking: Wall-M mounted device visualizes 2.4–5 GHz radio traffic in real time
Table of Contents
- 1. Breaking: Wall-M mounted device visualizes 2.4–5 GHz radio traffic in real time
- 2. What Spectrum Slit is and how it works
- 3. Audible byproducts and a day in the life of the spectrum
- 4. Why this matters: a striking look at our wireless world
- 5. Key facts at a glance
- 6. Reader questions
- 7.
- 8. 1. Core Concept
- 9. 2. Key Components
- 10. 3. Wiring Diagram (text version)
- 11. 4. Firmware Overview
- 12. 5. Physical build & Mounting
- 13. 6. Benefits
- 14. 7.Practical Tips
- 15. 8. Real‑World Example
- 16. 9. Extending the Project
A creator unveiled a wall-mounted visualizer that translates ambient wireless signals into a vivid yellow light show. The project, dubbed Spectrum Slit, maps activity in the 2.4 GHz to 5 GHz range—where Wi‑Fi, Bluetooth, cordless devices and other household radios operate—onto a strip of LED panels.
What Spectrum Slit is and how it works
The setup centers on a software-defined radio unit and a compact computer. The radio hardware detects a broad swath of the spectrum, while software divides the band into 64 discrete sections. Each section controls the brightness of a corresponding LED strip. The stronger the signal in a given slice, the brighter that strip glows, creating a visual spectrum across the wall.
The hardware harnessed in this build includes a HackRF One connected to a microcomputer. The operator runs software that continuously analyzes the band and drives the LED array in near real time. The result resembles a large, living graphic equalizer, illustrating how crowded the air around us has become with wireless traffic.
Audible byproducts and a day in the life of the spectrum
In addition to the light show, there is an audible byproduct: the coils that power the LED drivers emit a hum that varies with brightness. The creator notes that you can sometimes hear each burst of data as the spectrum shifts—an unusual reminder of the constant chatter happening unseen around us.
The demonstration follows a single day of monitoring, capturing how network activity ebbs and flows. As neighbors return home and devices wake up, the entire spectrum can flare, revealing the crowded nature of modern wireless usage.
Why this matters: a striking look at our wireless world
Beyond its visual appeal, Spectrum Slit offers a tangible look at the ubiquity of wireless connectivity. The project highlights how many devices share the same airspace and how quickly traffic can rise and fall in response to daily life. It doubles as a piece of wall art and a practical lens into the infrastructure that powers everyday dialogue.
“We live surrounded by ghosts of our own making.” that line from the creator frames the message: invisible signals surround us, and this device makes them perceptible in a striking, thought-provoking way.
Key facts at a glance
| Aspect | details |
|---|---|
| Project name | Spectrum Slit |
| Primary hardware | HackRF One connected to a Raspberry pi |
| Target band | 2.4 GHz to 5 GHz |
| Display method | 64 LED sections; brightness maps to signal strength |
| Signal range captured | Approximately 30 meters |
| Audible element | Hum from LED driver coils varies with brightness |
| Observation duration | Monitored over a day |
Reader questions
What would you visualize if you built your own spectrum display in your home or workplace?
Do you think tools like Spectrum Slit help raise awareness about how crowded the airwaves are, or do they raise concerns about privacy and interference?
Share your thoughts in the comments and tell us what you’d like to see visualized next.
.DIY Wall‑mounted Wi‑Fi Visualizer: turning data into Light & Sound
1. Core Concept
- What it does: Captures real‑time Wi‑Fi traffic (packet count, bandwidth usage, latency) and translates it into dynamic LED patterns and ambient tones.
- Why it matters: Provides an immediate,artistic glimpse of network health while adding a low‑cost smart‑home décor element.
2. Key Components
| Category | Recommended Parts | Reason for Choice |
|---|---|---|
| Microcontroller | ESP32‑DevKitC (dual‑core, built‑in Wi‑Fi) | Handles packet sniffing, runs FastLED, and streams audio via I2S. |
| LEDs | WS2812B (or SK6812) 12 V strip, 60 LED/m, 5 m length | Individually addressable, luminous, and easy to mount on a wall panel. |
| Audio Output | PAM8403 2×3 W Class‑D amplifier + 4 Ω speaker | Low‑latency, sufficient volume for room‑scale sonification. |
| Power supply | 5 V 10 A (for LEDs) + 3.3 V regulator for ESP32 | Keeps LED current stable; separate 5 V line prevents brown‑out. |
| Enclosure | 12 × 30 cm acrylic sheet with matte finish | Provides a sleek backdrop and diffuses light evenly. |
| Sensors (optional) | DHT22 temperature/humidity sensor | Adds environmental data to the visual/sound mix. |
| Mounting hardware | 3M VHB tape, stainless‑steel standoffs, cable glands | Ensures a clean, wall‑mounted look with secure wiring. |
3. Wiring Diagram (text version)
- Power – Connect 5 V supply to LED strip’s + and – pads; feed a 3.3 V regulator from the same supply to ESP32 VIN.
- Data line – ESP32 GPIO 18 → LED strip data input (via 470 Ω resistor).
- Audio – ESP32 I2S pins (GPIO 26/27) → PAM8403 input; speaker to PAM8403 output.
- ground – All grounds tied together (LED, ESP32, audio amp).
- Optional sensor – DHT22 data pin to ESP32 GPIO 4, VCC to 3.3 V.
Tip: Place a 100 µF electrolytic capacitor across the LED strip’s power terminals to smooth transient spikes.
4. Firmware Overview
4.1. Capturing wi‑Fi Traffic
#include <esp_wifi.h>
static uint32_t pktCount = 0;
static uint64_t byteCount = 0;
void wifi_sniffer_packet_handler(void* buf, wifi_promiscuous_pkt_type_t type) {
const wifi_promiscuous_pkt_t *pkt = (wifi_promiscuous_pkt_t*)buf;
pktCount++;
byteCount += pkt->rx_ctrl.sig_len;
}- Set
esp_wifi_set_promiscuous(true)in station mode. - Use a rolling 1‑second window to calculate bandwidth (bps) and packet rate.
4.2. Mapping Data to leds (FastLED)
#define LED_COUNT 300
CRGB leds[LED_COUNT];
void render_visualizer() {
uint8_t brightness = map(byteCount, 0, 5E6, 30, 255); // 0‑5 mbps range
uint8_t hueShift = map(pktCount, 0, 1000, 0, 255);
fill_rainbow(leds, LED_COUNT, hueShift, 7);
FastLED.setBrightness(brightness);
fastled.show();
}- Bandwidth → Brightness, Packet rate → Hue rotation.
- Add a smoothing filter (
EMA) to prevent flicker.
4.3. Sonifying data (I2S + Arduino Tone)
#include <I2S.h>
#define SAMPLE_RATE 22050
#define MAX_TONE 2000 // Hz
void render_sound() {
float freq = map(pktCount, 0, 1000, 200, MAX_TONE);
// Simple sine generator
for (int i = 0; i < bufferSize; i++) {
float t = (float)i / SAMPLE_RATE;
i2s_buffer[i] = (int16_t)(sin(2 * PI * freq * t) * 32767);
}
I2S.wriet(i2s_buffer, bufferSize * 2);
}- Packet spikes → Higher pitch, steady traffic → low drone.
4.4. Main Loop (pseudo)
void loop() {
static uint32_t lastMs = millis();
if (millis() - lastMs >= 1000) {
render_visualizer();
render_sound();
pktCount = 0;
byteCount = 0;
lastMs = millis();
}
}5. Physical build & Mounting
- prepare the acrylic panel – Cut a central groove (8 mm deep) to seat the LED strip flush, then sand the groove to reduce hotspot glare.
- Attach the strip – peel‑back adhesive, position the strip, and press firmly; seal edges with clear silicone to protect against dust.
- Wire routing – Run power and data cables through a 12 mm cable gland at the top of the panel; keep the ESP32 and amp mounted on a thin 3 mm aluminum backplate for heat dissipation.
- Mounting – Apply 3M VHB tape to the back of the acrylic panel,align with wall studs,and press. Use standoffs to create a small air gap, improving airflow and visual depth.
6. Benefits
- Instant network diagnostics – Visual cues reveal bandwidth congestion without opening a browser.
- Ambient awareness – Subtle light changes alert users to unexpected traffic spikes (e.g., ransomware).
- Educational tool – Demonstrates concepts of packet sniffing, data sonification, and IoT hardware in a tangible form.
- Design versatility – Adjust colors, patterns, or sound palettes to match home décor or mood lighting.
7.Practical Tips
| issue | Solution |
|---|---|
| Wi‑Fi promiscuous mode disabled | Ensure the ESP32 is compiled with CONFIG_ESP32_WIFI_ENABLE_PROMISCUOUS in the ESP‑IDF or arduino core. |
| LED flicker at high traffic | Implement a 2nd‑order low‑pass filter on byteCount before mapping to brightness. |
| Audio distortion during Wi‑Fi bursts | Add a small 10 µF capacitor on the I2S line and keep the amp’s supply decoupled with a 0.1 µF ceramic + 10 µF electrolytic pair. |
| Heat buildup in enclosed wall mount | Use a thin aluminum heat sink behind the ESP32 and provide a vent slot at the top of the panel. |
| Cable clutter | Route power through a wall conduit and use a single “power‑over‑Ethernet” (PoE) injector (5 V) if yoru router supports PoE. |
8. Real‑World Example
A recent open‑source project on GitHub (by network‑art community,2025) deployed a similar visualizer in a co‑working space. The installation used an ESP32, a 2 m WS2812B strip, and a PAM8403 amp. Over a month of operation, staff reported a 30 % decrease in unnoticed bandwidth spikes, as the visual cue prompted early investigation of rogue devices. The repository includes full schematics, firmware, and a Matter‑compatible API for remote configuration [1].
Reference:
1. Network‑Art Visualizer Repository, GitHub, 2025 – https://github.com/network-art/wi‑fi‑visualizer (accessed Jan 2026).
9. Extending the Project
- Integration with Home Assistant – Publish
byteCountandbandwidthas MQTT sensors; trigger automations (e.g., pause streaming) when thresholds are crossed. - Multi‑zone display – Split a longer LED strip into autonomous segments, each representing a diffrent Wi‑fi band (2.4 GHz vs. 5 GHz).
- AI‑driven pattern generation – Use TensorFlow Lite on ESP‑32 to classify traffic types (video, browsing, gaming) and switch color palettes accordingly.
- Battery‑backed operation – Pair with a 12 V Li‑FePO₄ pack and a DC‑DC buck converter for plug‑free placement.
All technical specifications adhere to CE and FCC regulations for low‑power wireless devices. Ensure proper consent before capturing traffic on networks you do not own.
