The Zenmuse S1 is DJI’s first dedicated spotlight for its enterprise drone platforms. Built around LEP (Laser Excited Phosphor) technology, the S1 offers multiple lighting modes and supports remote-control adjustments via the DJI Pilot 2 app. Its operating range extends up to 500 meters, depending on the lighting mode used. This is expected to provide improved visibility for night-time missions involving infrastructure inspections, public safety surveillance, and search and rescue tasks.
Meanwhile, the Zenmuse V1 serves as DJI’s first aerial speaker payload, with a maximum broadcast range of up to 500 meters and a peak volume of 127 dB. It supports three communication modes: live voice recording, text-to-speech conversion, and playback of pre-recorded audio files. With directional broadcast control and environmental noise reduction, the system is built to support coordinated emergency response, evacuation communication, and tactical law enforcement operations.
In the context of the Middle East, where infrastructure development and urban safety operations are ongoing priorities, both payloads are expected to support specific operational use cases.
In power and utilities, the S1 may assist with inspections in low-light conditions and emergency assessments of power lines, substations, and electrical towers, particularly in remote or desert regions. Current operations often rely on daylight hours or additional manual lighting setups; a drone-mounted spotlight offers an alternative for time-sensitive maintenance or fault response missions after dark.
In oil and gas, the ability to illuminate isolated equipment such as flare stacks, storage tanks, and pipeline segments during low-visibility conditions may reduce inspection delays and improve documentation under tight operational windows. The S1’s beam control and energy efficiency could support operators in areas with limited infrastructure lighting.
In public safety and emergency response, law enforcement and civil defence units in cities like Dubai, Abu Dhabi, and Riyadh may deploy the V1 to issue evacuation orders, direct search teams, or guide individuals to safety during natural disasters, fires, or industrial accidents. The V1’s compatibility with pre-recorded or automatically generated speech also allows for multilingual communication in densely populated or diverse urban zones.
For search and rescue teams, the S1 provides visual coverage over wide areas at night, while the V1 can be used to communicate with individuals located or in distress. This may be especially relevant in mountainous or coastal areas, where ground access is limited and visibility is poor.
The Zenmuse S1 and V1 payloads’ inclusion in the existing DJI enterprise ecosystem means operators can integrate the payloads without extensive modifications to approved flight frameworks or airspace authorisation processes.
Both payloads carry an IP54 rating, making them suitable for outdoor use in dust-prone or humid environments common across the Middle East. The S1 operates within a temperature range of -20°C to 40°C, while the V1 extends to 50°C, allowing both tools to function under typical summer field conditions across the Gulf region.
From a hardware perspective, each payload is lightweight, under 1 kg, and supports flexible mounting configurations, including single or dual downward gimbals and single upward gimbal options. This allows operators to configure drones for simultaneous use with other sensors or tools.
While the Zenmuse S1 and V1 have not yet seen full-scale deployment across regional fleets, initial feedback from drone service providers and pilots has been exceedingly positive, focusing on integration feasibility and mission-specific planning.
In the meantime, their release signals a growing emphasis on drone-based night operations and active intervention capabilities, beyond the traditional imaging and mapping roles. As urban growth, infrastructure management, and emergency readiness continue to shape operational priorities in the Middle East, the integration of illumination and aerial audio payloads into drone systems reflects a broader shift towards real-time, field-level response from the air.
