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IoT / Edge AI

Papaya Smart Parking Meter

Building the Foundation for Urban Mobility

98.5%

Occupancy Accuracy

+35%

Revenue Increase

<200ms

Latency

5

Concurrent Models

Project Overview

  • Revolutionizing urban parking infrastructure with AI-ready edge devices.
  • AI-driven edge intelligence for real-time processing and analytics.
  • Mobile app for booking, payment, and live vehicle video feed.
  • Deployed in 2 Countries.

Challenges

Urban Congestion

Cities lacked real-time parking occupancy data, causing traffic congestion and revenue loss.

Manual Monitoring

Traditional parking meters offered no smart detection or analytics capabilities.

Security Concerns

Tamper detection and secure communication were essential for public infrastructure.

Scalability

System needed to scale across multiple cities and countries with varying requirements.

High-Performance Edge Platform

  • NVIDIA Jetson AGX Orin 32GB — 200 TOPS AI performance.
  • 8-core ARM CPU, 32GB LPDDR5 RAM, 1792-core Ampere GPU with 56 Tensor Cores.
  • TensorRT and dedicated DLA for accelerated inference.

Comprehensive Sensor Suite

  • LiDAR: Solid-state for high-accuracy spatial mapping and 3D position estimation.
  • Camera: 4K high-resolution with low-light capabilities.
  • Ultrasonic Sensors (4x): Proximity and movement detection.
  • Environmental Monitoring: Temperature, humidity, barometric pressure, air quality.
  • NFC Reader for contactless payment and Dual-band RFID for vehicle identification.

Edge Intelligence & AI Models

  • Vehicle Detection and tracking at high speed.
  • License Plate Recognition with multi-region support.
  • People Detection including loitering and wheelchair detection.
  • Tamper Detection using multi-modal sensor inputs.
  • Sensor Fusion with Kalman Filter for improved accuracy.
  • Predictive Analytics for occupancy forecasting and peak hour analysis.

Technology Stack

NVIDIA JetsonTensorRTDeepStreamDockerMQTTThingsBoardAWS S3Redis

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