Aiops 수자원 관리 플랫폼 by Xiaoxi Wang is a highly esteemed winner of the very prestigious 2024 A' Design Award 동상 in 웹사이트 및 웹 디자인 Competition Category.

동웹· 2024

Aiops 수자원 관리 플랫폼

by Xiaoxi Wang

Client: Xiaoxi Wang

A' Design Award 동상 Winner in 웹 Category

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Verified Award Winner

Verify Award Status for #152675

View at A' Design Award Press Release Award Badge

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The Design

About Aiops 수자원 관리 플랫폼

Aiops는 도시 상수도 네트워크를 위해 개발된 수자원 관리 플랫폼이다. 이 플랫폼은 사물인터넷 센싱, 빅데이터, 클라우드 컴퓨팅, 인공지능을 결합해 매설 배관을 포함한 수도 설비를 실시간으로 모니터링한다. 고장이 발생하면 즉시 보고되어 열악한 환경에서의 점검 필요성을 줄여준다. 인터페이스는 2.5D 지도와 간결한 아이콘을 활용해 데이터의 가독성을 높였으며, 관리자별로 레이아웃을 자유롭게 구성할 수 있다. Aiops는 스마트 스케줄링을 지원하고 물 낭비를 줄이는 데 기여한다.

The Recognition

About the A' Design Award 동상

Aiops 수자원 관리 플랫폼, 이 작품은 A' Design Award 동상 수상작으로, 창의성, 독창성, 영민함으로 돋보이는 뛰어난 디자인에 수여되는 높은 권위의 인정입니다. 동상 수상작은 충분히 숙련되고 인상적으로 창의적인 작품으로, 디자이너의 폭넓은 경험, 상상력, 기지를 입증합니다. Aiops 수자원 관리 플랫폼, 이 작품은 높이 평가받고 감탄과 사랑을 받는 사물로서 두드러지게 전문적이고 혁신적일 것으로 기대됩니다. 이 동상 수상 디자인은 예술, 과학, 디자인, 기술의 모범 사례를 담고 있으며 세부에 대한 주의로 훌륭합니다. Aiops 수자원 관리 플랫폼, 이 작품은 필요를 훌륭하게 충족하고 욕망에 닿으며 감정을 매료하고 호기심을 불러일으킵니다.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: This is a standardized, professional solution to water management issues. It incorporates advanced technologies such as IoT sensing, big data, intelligent control, cloud computing, AI, digital twinning, AI algorithms, and VR. With a robust monitoring system and data infrastructure, it achieves smart and secure allocation of urban water resources while preserving water ecology and environment.
Tags: intelligent water management platform, IoT, data visualization, optimized water allocation, monitoring of water equipment in real time
Production Technology: The platform features an interactive interface that adopts a 2.5D GIS map and 2D icons, making the data more intuitive and reducing the cognitive load of users. Its interface, icons, and quick functions can be personalized and customized according to the preferences of the managers. It also provides distinctive visualized data images, enabling a customized operating mode for individual users.
Design Challenge: In comparison to traditional water management systems, this platform offers instantaneous monitoring of concealed water equipment, prompt fault feedback, and intelligent control of start and stop times to ensure safe equipment operation. With a unified control and hierarchical coordination architecture, the platform facilitates synchronized management and optimization of operational data across various processes and management workflows.
Research: Water wastage is a prevalent issue in urban water network management across various stages. To optimize water resource allocation, comprehensive analysis is necessary for each stage. However, traditional data analysis methods in water management are cumbersome, and data gaps between different systems hinder the realization of full potential of data. This has created a greater demand for comprehensive water management platforms among managers.
Inspiration: Urban water pipelines require regular inspections, presenting challenges due to the complex layout of water networks and the inconvenience of inspections. Additionally, some harsh environments hinder human detection and data collection. This platform is specifically designed to address these challenges and optimize the unified management of urban water networks and water resource allocation. It aims to assist managers in optimizing water management strategies and reducing water wastage.
Project Duration: The project was initiated in Beijing in February 2021 and officially launched in August 2021.
Operation Flow: Instantaneous data aggregation and intuitive reporting are key features of the platform. Managers can effortlessly monitor the overall and local operational status of the system through the data visualization cockpit. This enables smart scheduling, online control, and prompt emergency responses from the water source to the end users, maximizing social, economic and environmental benefits.
Team Members: Xiaoxi Wang