How has DJI positioned its unmanned drone airports as the infrastructure driving China’s low-altitude economy into its mid-game—following the State Council’s 2024 elevation of the sector and provincial trillion-yuan targets—and what do its deployment results, including more than

DJI is positioning its docks less as drone accessories than as always-on, networked public-and-industrial infrastructure: a standardized physical layer for sensing, dispatch, data capture, and remote operations. The commercial shift is from selling aircraft for occasional projects to supporting recurring missions where flying is operationally necessary—public safety, infrastructure inspection, surveying, emergency response, and city management.

• Evidence of operational scale: Reporting attributes more than 8 million autonomous sorties, over 2 million flight hours, and deployment across 500-plus cities in 80-plus countries to DJI’s dock network since 2022. The important implication is that the bottleneck is moving from airframe capability to reliable scheduling, maintenance, regulatory approval, data workflows, and multi-user utilization. 16

• Wuhan illustrates the infrastructure thesis. Its “Smart City Eye” network comprises 146 unattended docks, spaced at roughly 2–3 km in core areas and 4–5 km elsewhere, with a claimed sub-five-minute response to nearly any non-restricted location. It serves 16 municipal departments rather than being owned separately by each one. 1416 That shared network is the economic argument: one city-funded base layer can serve police, environmental, water, land, construction, and emergency users while maintaining data and permission separation. 16

• The “cannot-not-fly” use case is what makes the model durable. In Wuchang, where daily traffic reaches roughly 900,000 vehicle movements, drones reportedly handle nearly 1,000 traffic incidents annually. In elevated-road incidents, about 30% of roughly 400 cases were reportedly resolved through remote loudspeaker instructions to photograph and move vehicles, avoiding an officer’s on-site response. 14 These are repeatable, time-sensitive tasks with measurable avoided labor, response-time, congestion, safety, or outage costs—not demonstration flights.

• Who pays: In this model, municipal government or a state-owned critical-infrastructure operator is the natural anchor purchaser because it can aggregate demand across departments and justify coverage as public infrastructure. A credible next step is “drone-infrastructure-as-a-service”: an operator funds, deploys, maintains, schedules, and assures the dock network; agencies or utilities buy mission capacity, response coverage, data products, or service-level outcomes. That depends on sustained utilization, flight permissions, safety accountability, and data-governance rules—not merely dock sales.

• DJI’s platform posture is deliberately horizontal. Its Cloud API allows DJI aircraft and docks to connect to third-party cloud platforms rather than requiring every user to develop a dedicated app; DJI says the API is intended to lower the barrier to third-party-platform access. 47 The technical design uses standard protocols including MQTT, HTTPS, and WebSocket to abstract device complexity, allowing integrators to retain the vertical workflow, data model, and customer relationship. 10

• Strategic consequence: DJI can remain the hardware-and-control substrate—aircraft, dock, device management, APIs—while system integrators own the domain applications for policing, utilities, surveying, or city operations. This reduces DJI’s need to become a specialist software vendor in every vertical and makes its devices more attractive to organizations that need local or proprietary platforms.

• “Internet of Drones” is the end-state, not yet a demonstrated nationwide utility. The analogy is a network in which many docks coordinate availability, routing, charging, task priority, airspace constraints, and handoffs much like network nodes manage packets. DJI’s API architecture and dock-to-cloud support are enabling components of that vision. 410 But city-scale coordination also requires interoperable air-traffic management, robust beyond-visual-line-of-sight approvals, cybersecurity, privacy controls, and viable operating economics.

Two cautions: I found solid support for the Wuhan deployment and DJI’s open-API approach, but insufficient independent evidence in the available results to validate the specific State Grid Taizhou 207-dock/6,434-km/every-three-days claim, the Nansha 36-dock/100%-uptime claim, or the asserted integration with “more than 1,000” third-party platforms. DJI’s own recent material instead cites 750-plus developers having built cloud platforms since the Cloud API’s 2022 release. 10