ESP32 → AWS → TechnikBrain dashboard
See the whole path, from sensor lead to S3 bucket.
Use this open-source tracker stack as your roadmap: wire the ESP32 DevKitC, push data to AWS S3, and watch the website turn raw telemetry into ride insights. The page below focuses on real connections—no need to decode every pin.
- Device clarity: connection-ready wiring for GPS, sensors, LEDs, and cellular.
- Cloud clarity: which S3 buckets we use, what lands there, and how the site reads it.
- Step-by-step: prerequisites in plain language so anyone can get started.
Sensor → Cloud runway
🛰️ ➜ 🧠 ➜ 📶 ➜ ☁️ ➜ 🪣
Edge fusion, TLS uplinks, and KMS-protected storage keep every hop auditable.
Live status lane
⚡ Low-power windows • 🔁 Backoff • 🛰️ PPS lock
Edge analytics highlight GPS lock, battery health, and firmware version before sync.
What you can build
• Real-time ride dashboards with S3-backed history and OTA firmware control.
• Secure telemetry that stays encrypted from sensor to browser.
• A developer-friendly pipeline you can fork, remix, and extend.
🛰️
Capture
Sensor fusion + PPS
Sensor wiring (ready-to-connect)
Skip the full pinout. Use these pairings to wire the exact sensors on the tracker.
Neo-6M GPS
UART2 (3V3 logic)
- TX → GPIO16 (RX2)
- RX → GPIO17 (TX2)
- VCC → 3V3
- GND → GND
Position, speed, and a clean PPS signal for timestamps.
BME280 (temp / humidity / altitude)
I²C
- SCL → GPIO22
- SDA → GPIO21
- VCC → 3V3
- GND → GND
Ambient readings plus barometric altitude for ride context.
MPU6050 (gyro + accel)
I²C (shared with BME280)
- SCL → GPIO22
- SDA → GPIO21
- INT → GPIO27
- VCC → 3V3
Crash/lean detection, smoothing for speed/heading jumps.
Status LEDs / light ring
GPIO
- Data → GPIO4 (WS2812B)
- Power → 5V or 3V3 as supported
- GND → Shared return
Rider cues for GPS lock, cloud sync, and alerts.
Battery monitor (optional)
ADC
- Sense → GPIO34 with divider
- GND → Shared return
Reads pack voltage for low-power behaviors.
Memory Layout
Typical DevKitC memory configuration with optional PSRAM. Adjust flash partitions for OTA and assets.
Flash (external SPI/QSPI) 2–16 MB — Firmware, static assets, filesystem (SPIFFS/LittleFS).
PSRAM (optional external) 2–8 MB — Frame buffers, ML features, caching web payloads.
Instruction RAM (IRAM) 192 KB — Hot code executed by both cores; Wi‑Fi/BT stacks.
Data RAM (DRAM) 320 KB — Heap, globals, FreeRTOS objects, DMA buffers.
RTC Fast/Slow RAM 8 KB / 8 KB — Low‑power retention variables, deep‑sleep context.
• Flash is split into bootloader, partition table, NVS, factory app, OTA slots, and optional SPIFFS/LittleFS.
• PSRAM maps into external address space; configure CONFIG_SPIRAM in menuconfig and enable malloc caps for buffers.
• Keep ISR‑bound code in IRAM (IRAM_ATTR) and DMA buffers in contiguous DRAM with 4‑byte alignment.
• RTC Fast RAM persists across deep sleep; RTC Slow RAM survives resets if not powered down.
Connectivity modules
Where the ESP32 links out to the world and how to wire each module.
SIM800L GSM
UART1 + GPIO reset
- TX → GPIO26 (RX1)
- RX → GPIO25 (TX1)
- RST → GPIO33
- VBAT → 3.7–4.2V with bulk cap
- GND → Shared return
Cellular uplink for telemetry/commands when Wi‑Fi is absent.
MicroSD (buffer)
SPI bus
- CLK → GPIO18
- MISO → GPIO19
- MOSI → GPIO23
- CS → GPIO5
Offline queue for telemetry and crash logs when the network is down.
Debug / USB serial
UART0 + USB
- TX0/RX0 → on-board USB bridge
- EN → reset button
Console logs, flashing, and recovery without opening the enclosure.
Flow from sensors to cloud
A simple, emoji-guided runway with advanced methods baked in: sensors → ESP32 → GSM → website → S3.
🛰️
Sensors
Neo-6M GPS, BME280, MPU6050, LEDs capture rich signals.
✨ Sensor fusion + PPS timestamping
🧠
ESP32 (firmware)
Samples over UART/I²C/SPI with filtering, buffering, and IDs.
✨ On-device ML smoothing + ring buffers
📶
SIM800 GSM
Publishes HTTPS via cellular with adaptive retries.
✨ Presigned HTTP with adaptive retries
☁️
Website & API
Consumes signed URLs or callbacks, powers dashboards and OTA toggles.
✨ Edge cache + WebSockets
🪣
S3 bucket
Versioned, encrypted objects store telemetry, firmware, and assets.
✨ KMS + lifecycle tiering
Device → Cloud → Website Data Flow
Sequence from a modern web UI to ESP32 firmware, covering transport, processing, storage, and how the dashboard uses it.
Website → ESP32 (Download)
Frontend makes HTTPS/WS call to API endpoint; ESP32 polls REST or maintains WebSocket for commands/firmware.
ESP32 Processing
Task splits workloads: sensor sampling, filtering (IIR/median), debouncing inputs, composing JSON payloads.
ESP32 ↔ Peripherals
I2C/SPI/UART drivers fetch sensor data; timers and interrupts align sampling; DMA used for high‑speed buses.
ESP32 → AWS (Upload)
HTTPS publishes telemetry, streaming logs over WebSocket; retries/backoff ensure delivery to S3-backed pipelines.
AWS → Website
APIs read processed objects from S3 and DynamoDB/MySQL, hydrate dashboards, and trigger OTA readiness flags.
Storage & Memory Hygiene
Ring buffers for telemetry, PSRAM for large blobs, flash partitions for OTA slots and configuration.
Security: HTTPS + JWT/OAuth tokens for APIs, certificate validation, TLS everywhere. Use unique client certificates/keys and rotate credentials.
Reliability: Exponential backoff, idempotent commands, and versioned configs. Cache latest command in NVS to replay after brownouts.
Performance: Batch sensor samples, compress JSON (e.g., CBOR), and keep Wi‑Fi active windows short when battery powered.
Interactive end-to-end data workflow
Click a stage to see what happens at each hop—from sensing on the ESP32 to visualizing inside the website.
1) Collect
Sensors capture GPS, motion, power, and crash events on the ESP32.
Fast tasks run on timers/IRQs; noisy values are smoothed (IIR/median) before being packed into JSON.
Telemetry
OTA-ready
Secure defaults
AWS + S3 in plain language
Where data lands, why it is safe, and how the website reads it.
tb-telemetry (S3 Standard)
Ride JSON, GPX/GeoJSON tracks, device logs, crash breadcrumbs.
Ops tips: Versioning on, lifecycle to Glacier after 90 days, KMS encryption with unique prefixes per device.
tb-firmware-artifacts
Signed OTA binaries, manifest JSON, integrity hashes.
Ops tips: Private access with presigned URLs, object lock optional for golden images, checksum verification on download.
tb-web-assets
Marketing images, docs, and diagrams (like this page) served via CloudFront.
Ops tips: Cache-control headers tuned for speed, compression enabled, invalidations on release.
How the website uses your data
- Shows live ride maps and charts by reading processed GeoJSON/JSON from the telemetry bucket.
- Highlights health checks (battery, storage, connectivity) from periodic status blobs the ESP32 posts.
- Surfaces OTA readiness by checking firmware manifests and hashes stored next to the binaries.
- Provides download/export (CSV/GPX) straight from S3 with time-bounded, signed URLs.
What you see as a rider or admin
- Plain-language summaries: “Last sync 3m ago”, “Firmware v1.2.3 installed”, “GPS lock healthy”.
- Privacy controls to wipe telemetry and revoke device credentials without touching the hardware.
- Auditability: every upload is versioned, and a trail of who pulled data is logged via CloudTrail/Server Access Logging.
Data path to the website: a small API layer (PHP/Lambda) reads the latest ride objects in S3, normalizes units, and stores summaries in the database so charts and maps load instantly.
Privacy-first defaults: everything is encrypted at rest (S3 + KMS) and in transit (TLS), and you control retention via lifecycle rules.
Prerequisites to run the open-source tracker
Start simple, then grow into advanced AWS features.
- Create an AWS account and IAM user with programmatic access (no root keys in code).
- Provision the three S3 buckets above, enable default encryption, and turn on versioning for telemetry + firmware buckets.
- Generate an IAM policy scoped to the buckets and attach it to the device/CI user; restrict uploads to per-device prefixes.
- On the ESP32, flash Wi‑Fi credentials and HTTPS endpoint; import TLS root CA and client certificate if using mutual auth.
- On the website, set environment variables (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_DEFAULT_REGION`, `AWS_TELEMETRY_BUCKET`, `AWS_FIRMWARE_BUCKET`) and test with a single device upload.
- Optionally wire AWS IoT rules to drop messages straight into the telemetry bucket or invoke a Lambda that cleans and tags payloads.
From starter kit to production
Begin with a breadboarded ESP32, then scale into AWS with the same pipeline.
Beginner
- Connect sensors to the pins above and print JSON over USB.
- Push sample payloads to
tb-telemetry with a presigned URL.
- Open this website to see the data echoed back.
Intermediate
- Harden HTTPS uploads with presigned URLs and backoff; monitor delivery metrics.
- Turn on OTA: store BIN + manifest in
tb-firmware-artifacts and let the ESP32 poll.
- Add alarms for missed heartbeats using CloudWatch Metrics + Alarms.
Advanced
- Use Kinesis/Lambda to enrich telemetry (e.g., weather, map matching) before it lands in S3.
- Serve dashboards via CloudFront + signed cookies; push anonymized datasets to analytics.
- Adopt multi-region replication for high availability and faster OTA near riders.
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