Call D.A.N.I. (Decentralised Autonomous Nomadic Infrastructure)


Name: Patrick Macasaet

Nationality: Australian

Institution / Company: SUPERSCALE, RMIT Architecture


Name: Vei Tan

Nationality: Malaysian

Institution / Company: SUPERSCALE


Name: Ezra Macasaet

Nationality: Australian

Institution / Company: SUPERSCALE


-HONOURABLE MENTION of Hong Kong Drone Port Competition


Year 2036. D.A.N.I HK walk tour. Tour leader: Ezra.


“… Gather around everyone. This is D.A.N.I Drone-Port no.291019, part of the ‘Decentralised Autonomous Nomadic Infrastructure’ unit… Came to fruition late-2020s to combat rising urban congestion and its effect to our emergency services and diminishing public spaces. They house our autonomous emergency drones and dispersed throughout the city network – extending our public service infrastructure.


It capitalises on social media’s community-led journalism and reporting. Old news is no news. The real information is on ground – collected, dissected, and curated real-time posts from community are fed through the ‘Emergency Data Epicentre Network’ or EDEN for short then sorted by AI machine learning. Consistent data that cluster within the network is forwarded to the nearest D.A.N.I. drone, sent out first and communicate what’s needed – police, fire, paramedic, community force, whatever.


They consist of 3 modules – mast, egg, and capsule. Each port is different based on site conditions. Below the egg is a flexible civic space. They’re quite nice and views infrastructure as civic. They stand out, proud and ever visible but comfortably watching like another piece of street infrastructure. ‘We’re here looking out for you’ as if to say. They’re bright, cheery but serious. If you’re in trouble, just call D.A.N.I.”


#emergencies #publicspace #autonomous #urbanregeneration #decentralised


Jury Comments

– Anastasia Prosina

“Call DANI”, a drone platform that responds to the public’s immediate needs through social media postings, brings public services to literally “new heights.” This platform addresses the most inefficient city processes — the delivery of emergency services, critical medical supplies, perishable high-value goods, and time-sensitive documents, by combining the sophistication and efficiency of AI and the quick travel by air vs. congested city streets.

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