ESP32-Paxcounter
An ESP32-based device that counts people by detecting nearby WiFi and Bluetooth signals, with optional LoRaWAN, MQTT, and sensor data logging.
What is ESP32-Paxcounter?
ESP32-Paxcounter is an open-source firmware that turns ESP32 LoRa boards into people-counting and multi-sensor nodes. It estimates crowd sizes by scanning for nearby WiFi and Bluetooth signals from mobile devices, solving the need for affordable, privacy-respecting passenger flow metering in public spaces, retail, or events. The project also integrates environmental sensors and supports multiple data transmission methods like LoRaWAN and MQTT.
IoT developers, makers, and researchers who need to monitor people density or collect sensor data in real-time using low-cost hardware, especially in scenarios where privacy and battery life are important.
Developers choose ESP32-Paxcounter because it offers a ready-to-deploy, privacy-focused solution for people counting without expensive proprietary systems. Its support for multiple data outputs, sensor integration, and deep sleep optimization makes it versatile and energy-efficient for field deployments.
Overview
Wifi & BLE driven passenger flow metering with cheap ESP32 boards
Use Cases
Best For
- Monitoring foot traffic in retail stores or public venues
- Estimating crowd sizes at events or transportation hubs
- Building battery-powered environmental sensing stations with people-counting capabilities
- Creating low-cost IoT nodes for smart city or occupancy analytics
- Privacy-respecting people density measurement in offices or buildings
- Educational projects on IoT, LoRaWAN, and embedded sensor networks
Not Ideal For
- Applications requiring precise, individual-level people tracking (e.g., access control systems or ticket validation).
- Real-time monitoring systems needing sub-minute latency and high data throughput over cellular or Wi-Fi networks.
- Teams wanting a fully managed, SaaS-based people counting solution without hardware maintenance or firmware customization.
Pros & Cons
Pros
Does not persistently store MAC addresses or fingerprint devices, ensuring anonymous counting that aligns with ethical data collection practices.
Leverages ESP32 deep sleep mode for extended operation on a single 18650 Li-Ion cell, enabling long-term deployments in field settings.
Supports SD-card logging, LoRaWAN transmission (e.g., The Things Network), MQTT over TCP/IP, and serial communication, offering versatility for different IoT workflows.
Can read and store data from various environmental sensors alongside people counts, making it a comprehensive sensing node for crowd and environmental monitoring.
Cons
Optimized for specific ESP32 LoRa boards like LILYGO®, limiting compatibility and requiring firmware adjustments for other hardware, which adds complexity.
Relies on detecting mobile device signals; accuracy is affected by devices with WiFi/Bluetooth turned off or environments with multiple devices per person, making it unsuitable for exact counts.
Requires configuring ESP32 firmware, LoRaWAN networks, and sensors, which can be challenging for those new to embedded systems or without prior IoT experience.
Frequently Asked Questions
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