Silevera Theknoloji ya Tlhahisoleseding · 2025
Holosentinel Sisteme ya Setjhaba se Bohlale
by Hey July
- Moputso oa Silevera oa A' Design Award 2025 in Theknoloji ya Tlhahisoleseding
- CLIENT: Hey July
- Estimated Number of Design Views: 81,501
- Verification code C53C25BC37 · Verify this award
Colors
About Holosentinel Sisteme ya Setjhaba se Bohlale
Tsamaiso ya 3D ya Motswako e kopanya bohlokwa bo phahameng ba maemo a sebaka sa leratadima le ditaolo tse utlwahalang habonolo. Dikarolo tsa 3D di bontsha dibopuwa tsa mehaho le dikotsi tse fetohang, ha diphanele tsa 2D di sebedisa mokodiso wa mocheso ho hlokometsa tshebediso ya matla le tshebetso ya disebediswa. Mehlala ya boitshwaro ya AI e supa ka boithaopo dibaka tsa kotsi e phahameng, e nolofalletsa ho fumana tiragalo ka metsotswana e mehlano. Di-algorithm tsa sebaka di ntlafatsa HVAC le mabone ka mehlala ya mocheso wa batho ka 3D, e fokotsa tshebediso ya matla ka 30 phesente. Tsamaiso ka matshwao a letsoho e netefatsa diphetoho tse bonolo dipakeng tsa dipono tse kgolo le tse nyenyane, e fihlella dikatlego kutlwisisong ya interface le bokgoning ba tshebetso.
About the Moputso oa Silevera oa A' Design Award
Holosentinel Sisteme ya Setjhaba se Bohlale ke mohapi oa Moputso oa Silevera oa A' Design Award, kananelo e hlomphehang haholo e fuoang meralo e phahameng ka ho fetesisa, e ntle le e tsosang maikutlo. Bahapi ba Silevera ke mesebetsi e khanyang haholo le e nang le boqapi bo ikhethang e bontšang botsebi, talenta le bohlale ba baqapi ba eona. Holosentinel Sisteme ya Setjhaba se Bohlale e lebelletsoe ho ba mosebetsi o motle, oa mohlala, o nang le boprofeshenale bo bonahalang le mehopolo e mecha e tebileng. Moralo ona o hapileng Moputso oa Silevera oa A' Design Award ke mohopolo o hlokomelehang haholo le o ratoang o tlisang molemo mme o sutumelletsang meeli ea bonono, mahlale, moralo le theknoloji. Holosentinel Sisteme ya Setjhaba se Bohlale ke mosebetsi oo batho ba bangata ba o lakatsang, o tsosang litakatso, o tlisang maikutlo a matle le o tsosetsang ho makala le ho hlolla.
Press Kit
- Unique Properties
- Featuring a hybrid 2D and 3D interface with aerospace-grade clarity, the system offers an intuitive spatial view. The 3D layer highlights structures and risks like stalking alerts, while 2D panels show real-time energy and device status via thermal coding. Users can tap floor plans for details or swipe to shift views. AI-driven models detect high-risk zones, enabling five-second security responses. Spatial optimization cuts energy use by 30 percent, enhancing both visual cognition and operational intelligence.
- Dimensions & Packaging
- The System Is Compatible With Mainstream 16:9 Screen Ratios (e.g., 1920 x 1080, 3840 x 2160), Ensuring High-Clarity 3D Visualization Across Various Devices While Maintaining Spatial Accuracy.
- Tags
- Digital Twin Community Safety, 3D Visualized Security Intelligence, Vulnerable Group Spatial Protection, Millimeter-Accurate Energy-Saving Modeling, Cross-Dimensional Cognitive Interface
- Production Technology
- Utilizing precise one-to-one 3D modeling with sensor positioning accuracy of less than 2 cm, the system integrates real-time IoT data, including surveillance feeds and access logs, into its digital twin. Light and shadow physics enhance realism, while aerospace-grade mission color coding improves clarity: blue for security alerts, orange for energy issues, and a dark background for hierarchy. This design enables 0.3-second critical data recognition, ensuring seamless spatial-to-operational response.
- Design Challenge
- Internally, the Challenge Was to Develop a Fully Functional 3D Engine, AI Models, and UX Design Within Just Three Months. A Modular Architecture Was Implemented to Decouple the Real-Time 3D Framework From Backend Algorithms, Enabling Parallel Workflows That Reduced Development Time by 40 Percent. Externally, the Biggest Obstacle Was IoT Fragmentation Across Seven Different Protocols. To Address This, a Lightweight Middleware Was Created to Standardize Proprietary Protocols Into a Unified Data Stream. Automated Compatibility Testing Further Ensured Interoperability Among Six Major Security Brands, Effectively Bridging Ecosystem Silos.
- Research
- Type of Research: Applied Design Research.
Research Objectives: Validate digital twin technology for enhancing community safety and energy optimization.
Methodology: Mixed-methods integrating IoT sensor analytics with user behavior observation.
Data Collection/Tools: IoT sensor data and digital twin modeling for spatial data fusion.
Participants: 385 residents and 18 managers from a Beijing pilot community.
Results: Achieved 42% faster emergency responses and 27% reduced energy use.
Insights/Impacts: Predictive risk management redefines smart city governance, bolstering property tech, societal safety, and energy-efficient design. - Inspiration
- Leveraging Cutting-Edge Digital Twin Technology, This System Reconstructs Communities With Millimeter-Accurate 3D Modeling. Its Virtual Engine Analyzes Real-Time Data From Surveillance Cameras and Access Controls, Identifying Spatiotemporal Anomalies Such as Loitering Near Children's Areas for Proactive Crime Prediction. When Prolonged Inactivity Is Detected in Elderly Residents' Homes, the System Initiates Automated 3D Location Verification. By Transforming Fragmented Data Into Actionable Spatial Intelligence, It Evolves From a Passive Monitoring Tool Into a Proactive Guardian of Community Safety.
- Project Duration
- Development Began in September 2022, Followed by Pilot Testing in a Residential Community in Beijing. The System Was Successfully Deployed in January 2023.
- Operation Flow
- The System Supports Both Mouse and Tablet Touch Controls, Allowing Users to Navigate 3D Spatial Models, Access Operational Features, and Conduct Precise Searches Seamlessly.
- Image Credits
- Image #1 : Creator Gao Chao, Holosentinel, 2024.
Image #2 : Creator Gao Chao, Holosentinel, 2024.
Image #3 : Creator Gao Chao, Holosentinel, 2024.
Image #4 : Creator Gao Chao, Holosentinel, 2024.
Image #5 : Creator Gao Chao, Holosentinel, 2024.
Video Credits: Produced by Gao Chao, 2024.
