Baidu Safety Production パイプライン点検インターフェース by Baidu AI Cloud is a highly esteemed winner of the very prestigious 2023 A' Design Award 銀賞 in インターフェース・インタラクション・UXデザイン Competition Category.
銀インターフェース· 2023
Baidu Safety Production パイプライン点検インターフェース
Client: Baidu Online Network Technology (Beijing) Co., Ltd
A' Design Award 銀賞 Winner in インターフェース Category
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The Design
About Baidu Safety Production パイプライン点検インターフェース
Baidu Safety Productionは、石油・ガスパイプラインの点検を行うためのインターフェースである。人工知能を、インテリジェントデバイス、産業ビッグデータ、エッジコンピューティング、デジタルツイン技術、IoT、GISマッピング、5Gと組み合わせている。これにより、高リスク地域において無人または省人化された点検が可能となる。機能には、安全リスクの特定、異常事象の自動報告、三次元による遠隔監視が含まれる。ロボットと点検計画はコンピューター上で管理され、情報はモバイル端末や大型スクリーンにも表示される。
The Recognition
About the A' Design Award 銀賞
Baidu Safety Production パイプライン点検インターフェースは、見事で印象的なハイエンドのデザインに授与される、非常に権威ある評価である A' Design Award 銀賞の受賞作品です。銀賞の受賞作品は、きわめて輝かしく創造性に富んだ作品であり、デザイナーの傑出した専門知識、才能、洞察力を示しています。Baidu Safety Production パイプライン点検インターフェースは、素晴らしい代表作であり、驚くほどプロフェッショナルで、深く革新的であることが期待されます。この A' Design Award 銀賞を受賞したデザインは、非常に注目すべき称賛される発明であり、芸術・科学・デザイン・技術の境界に寄与し、それを前進させます。Baidu Safety Production パイプライン点検インターフェースは、多くの人に羨まれる創造物であり、欲求を呼び覚まし、前向きな感情をもたらし、驚きと感嘆を灯します。
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- This system achieves technological breakthroughs by deeply integrating AI with oil and gas pipeline inspection, while effectively improving inspection efficiency and realizing early accident warning. Additionally, it combines various intelligent devices and utilizes technologies such as industrial big data, edge computing, digital twin, the Internet of Things, GIS, and 5G to achieve unmanned or minimally manned inspections in high-risk scenarios.
- Dimensions & Packaging
- Robot, Large Screen, Android Mobile Device, Computer
- Tags
- System, Personal Safety, Artificial Intelligence, Social Services, Multi-Platform Interaction, User Experience
- Production Technology
- This system achieves deep integration of advanced technologies such as artificial intelligence, big data, the Internet of Things, GIS mapping, and digital twin with inspection scenarios. It provides users with functional services including intelligent identification of safety risks, automatic reporting of abnormal incidents, and 3D visual remote monitoring. The system achieves unmanned intelligent inspection and linkage of early warning for abnormal events, thus improving the safety quality of inspection.
- Design Challenge
- The pipeline inspection scenarios present several challenges, such as high labor intensity, poor operation quality, and difficulty in improving efficiency and ensuring personnel safety. Baidu inspection system was designed to solve these problems.
- Research
- During the early design phase, we conducted numerous user interviews and field research and discovered that the oil and gas pipe gallery contains many pipelines, as well as flammable, explosive, and toxic substances, making traditional manual inspections potentially unsafe. Baidu inspection system greatly improved inspection efficiency and ensured safety production.
- Inspiration
- In China, the transportation of pipeline for oil and gas is enclosed and complex, and the transport medium may include toxic gases such as hydrogen sulfide and benzene. Traditional patrol inspection mainly relies on manual labor, and once a leak occurs, it poses a huge safety hazard to personnel. Baidu developed this system in response to these challenges.
- Project Duration
- The project was designed in China in May 2022 and has since been implemented in Chinese enterprises in August. The process is still ongoing and being continuously updated to meet new requirements.
- Operation Flow
- Users can manage robots, develop inspection plans, and view and process any situation in the pipeline through PC terminals. They can also view information on mobile phones, large screens, and PCs. This multi-terminal linkage interaction reduces limits of time and space, improves the quality of inspection, and ensures the safety of personnel.
- Team Members
- Qianle Wu
Juan Xiong
Xin Yang
Lu Han
Mingzhi Wang
Tingting Wang
Youping Yu
Feng Huang
Mingfa Zhu
Hong Cheng - Image Credits
- Optional Image #4: Photographer Juan Xiong, illustration, 2022. Copyrights belong to Baidu Online Network Technology (Beijing) Co., Ltd, 2022.
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