Public transit (Bus, Rail, etc)

應用故事

Public transit (Bus, Rail, etc)

Real-time Rail Obstruction Recognition & Warning(Member only)

Discover how Neousys rugged embedded computers and power backup modules enhance railway safety with real-time object detection, driver monitoring, and stable performance under extreme conditions for modern intelligent transportation systems.

Autonomous Electric Train

Neousys' Nuvo GC series rugged AI computer powers autonomous trains, offering AI-driven solutions for predictive maintenance, object detection, energy efficiency, and real-time monitoring in challenging environments...

自動化汽車檢測系統

自動偵測系統採用Neousys的Nuvo無風扇電腦搭配PB-9250J-SA備用電源。透過 HMI 檢測多達 15 種不同類型的汽車零件，無需改變生產工序或硬體配置...

車輛到基礎設施鐵路平交道口入侵預警系統

鐵路平交道口事故經常發生且後果嚴重，為了防止事故發生，我們的一家客戶應用了新的系統利用車輛到路側通信向駕駛員發出即將來臨的火車警告...

電動巴士監控資訊系統

一家專注替代燃料的歐洲巴士製造商推出低噪音、零排放電動巴士，採用Neousys宸曜科技VTC強固車載電腦，整合多功能控制，實現全天候運行、高效穩定與低能耗，提升都市交通體驗...

Neousys In-vehicle Computer Leads the Way of Autonomous Delivery

Neousys VTC Series, A high-performance fanless in-vehicle system providing commensurate computing power for enabling AI-based autonomous vehicles, in a compact size increasing the volumetric efficiency of customer's vehicles...

自動駕駛大眾運輸

宸曜嵌入式計算平臺運算平台作為一台強大的主控器，在車輛行駛的過程中能夠處理所有來自子系統的資料，同時允許每個元件進行交互和執行操作，大大簡化了整個系統的基礎設施，使之成為一個高效和高性價比的解決方案。

Non-GPU Guided Autonomous Vehicle

With Neousys Nuvo rugged embedded systems, developers can create cost-effective autonomous vehicles that process imagery data with CPUs instead of GPUs. These systems offer a wide range of connectivity options and rugged features, making them an ideal choice for harsh environments.

集電弓監測系統

集電弓監測系統通過對圖像進行處理分析，分析集電弓的健康狀況，並在任何監測參數達到設定閾值時發送警告和通知，以便及時採取應對措施，避免維修拆卸。

列車安全中的嵌入式電腦部署：HOTT 及 EOTT 遠端監控如何確保安全煞車

列車車廂可能長達幾百米，試圖在列車全速前進過程中制動將會造成很大的危險。列車遙測系統通過對列車的即時監測、資料記錄和持續的設備間通信，降低意外發生時列車所面臨的危險。

Imagery Recognition & Automation for Harbor Cargo Ports

The Neousys system is installed on-site with wireless communication, cameras and relay actuators connected. Trucks' license plates entering/ leaving the port dock area are scanned; containers entering/ leaving the port dock area are scanned, coupled with the machine vision software recognition system where the recognition precision rate is up to 99% accurate.