AI at Blenheim Palace
Oxford Brookes and Blenheim Palace collaborate to boost sustainability and operations with innovative tech and data analytics.
Oxford Brookes University and Blenheim Palace have been collaborating to use innovative technologies and data analytics to enhance Blenheim's operations and promote sustainability. At a recent in-person Brookes Festival of AI event, held at Blenheim, attendees were invited to explore the sensor network and learn about the latest projects resulting from the partnership, including the creation of a Smart Visitor Management System.
During the event, David Green, Blenheim's Head of Innovation, talked about the difficulties involved in maintaining a historical property while addressing the potential of AI and machine learning to address some of these. He highlighted Blenheim’s a culture of innovation and how the Knowledge Transfer Partnership (KTP) with Oxford Brookes University helped utilise data and sensors to boost operations and improve customer experiences.
The Smart Visitor Management System was a key topic of discussion at the event, which was developed jointly by Oxford Brookes and Blenheim Palace. The system employs innovative technologies such as sensors that can transmit data up to five kilometres away, to forecast foot traffic and manage operations more efficiently.
Oxford Brookes played a crucial role in developing the system, utilising AI and machine learning to analyse the data generated by the sensors and providing real-time dashboards to monitor the effect of visitors on Blenheim and the local area. The system can also potentially integrate with building management systems, providing a comprehensive overview of operations.
In addition to the Smart Visitor Management System, Blenheim Palace also utilises innovative technologies to monitor and enhance the environment inside and outside the Palace. The project involved using vibration and air quality sensors to detect the impact of events on the environment, monitoring water quality in the lake, and employing multispectral imagery to comprehend changes in plant growth.