Smart Parking - EDGEMATRIX Inc.

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Edge AI Station α
Smart Parking

Edge AI Station α AI Application

｜App Features｜

Real-time congestion detection: Uses AI to analyze camera footage and determine the congestion status of the parking lot in real time.

Area usage monitoring: You can monitor the usage status of each parking area.

All-weather capability: AI-based measurement is possible even in light rain or snowfall.

｜App Intro Video｜

Applied to Smart Parking.(※Under development image.)

｜Usage Scenes｜

Monitoring Parking Lot Congestion

We monitor parking lot congestion at service areas, parking areas, and roadside stations, provide information to users, and enhance convenience.

Service areas
Parking areas

Large commercial facility

Tourist destination

Enhancing customer satisfaction and improving operational efficiency

Monitor parking lot congestion at shopping malls and restaurants to enhance customer satisfaction. Gain real-time visibility into congestion at coin-operated parking lots to improve operational efficiency.

Commercial facility

Hourly parking lot

Airports

｜App Overview｜

Real-time congestion detection is implemented with the following three functions:

Parked vehicle count

Usage statistics by
parking area

Detection of long-term parking and illegal parking

With Node-RED, a standard feature of AI Station, inference results from
AI applications can be processed and sent formatted for integration with external systems.

Generic Node-RED Flow (Post-Processing) Overview

Mail alert (sending)

Generic flow that periodically emails the vehicle count from the AI app's inference results.

*Customer mail server and mail account are required.

Since many AI Station use cases are expected to be deployed in on-premise environments or closed networks with no internet connection, the provision of web apps for visualization is optional for AI Station compatible apps (AIP), unlike the existing store apps (EAP). However, it is not necessary to provide a web app for visualization in an environment with internet access. However, for customers who install AI Station in an environment with internet access, we can provide a web app for visualization by sending the inference results to your website through post-processing by Node-RED. By preparing a web application for visualization, you can appeal your AI application to a wider range of customers, so we hope you will consider developing and providing a web application for visualization.

Grafana

*This screen is taken from the analysis screen of Kaleidoscope (a multifunctional people detection app).
We plan to use a general-purpose visualization system that can be built with OSS, consisting of Grafana + InfluxDB.
*We plan to provide a manual on how to build a general-purpose visualization system and a general-purpose Node-RED flow for sending visualization data to InfluxDB.
*Compliant with Grafana dashboard functionality.
※Real-time visualization of vehicle counts by vehicle type and entry direction is possible via graphs, tables, and other formats. The raw data used for visualization can also be downloaded in CSV format.

｜Function Details｜

Detection Methods

AI analyzes parking lot surveillance camera footage to count vehicles in designated areas in real time. The entire parking lot can be divided into customizable zones, allowing independent congestion detection for each area. For example, it can manage vehicle counts separately for “small vehicle zones,” “large vehicle zones,” “bus zones,” and more. Zone-based statistics enable analysis of parking lot usage trends and contribute to optimal zone-specific operations. Vehicles parked for extended periods within designated areas are automatically detected, triggering alert notifications when they exceed pre-set stay durations. Vehicles parked in monitored areas such as “No Parking Zones” or “Delivery-Only Zones” are also instantly detected.

App Provider Company

Company Name:EDGEMATRIX Inc.

About Us:We contribute to society through the development of “Video Edge AI” infrastructure technology. Our mission is to implement “Video Edge AI” in society.

URL:https://edgematrix.com/en

Edge AI Station brochure
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Implementing "Video Edge AI" into various fields.