Open Digital Platform Features

The ODP’s key features include:

• Communication with different smart city technologies
• Digital Twin of PDD
• Integration of building systems and services
• Real-time monitoring of district and facility systems and operations
• Data ingestion, transformation, and analytics

Communication with different smart city technologies

The ODP’s Open Standard Multiprotocol Middleware helps the platform to connect and communicate with different district management systems even if they utilise different communication technologies.

Digital twin of PDD

The workings of ODP can be visualised via a digital twin, which is a virtual representation based on a real-life 3D model of the PDD. This digital twin will include real-world data of the district, such as power consumption, weather forecasts, and temperature readings.

With the digital twin, developers are able to run simulations of real-world scenarios before actual implementations. For instance, developers can use it to test new products and processes such as training the software of autonomous vehicles.

Read more about PDD’s digital twin here.

Integration with building systems and building services

The ODP has been integrated with building systems that include:

• Elevator systems
• Escalator systems
• Building Air-Conditioning and Mechanical Ventilation (ACMV) systems
• Access control and security systems

It has also successfully been integrated with building services such as:

• Robotic delivery
• Electric vehicle charging stations
• Meeting room occupancy
• Temperature monitoring and control

Real-time monitoring of district and facility systems and operations

The ODP integrates real-time information from a network of sensors and IoT devices.

Data ingestion, transformation, and analytics

The ODP, via its Open Standard Multiprotocol Middleware, ingests data streams from various district management systems. These data streams will then be processed and transformed in real-time allow sense-making for greater situational awareness. It also analyses data from different systems and sensors and uses AI such as machine learning to predict and send commands to systems in response to real-world happenings.

Last updated 06 May 2024