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Conducting test flights with the DJI Neo drone reveals significant challenges when flying over water due to limited AI functionality. While it performs adequately on land, the drone’s AI tracking struggles with reflections on water, causing difficulties in reacquiring targets. Users are advised to switch to manual mode for improved control when over bodies of water. Despite these setbacks, the DJI Neo holds promise as a useful tool for capturing video, especially in scenic locations. Preparations are ongoing to take advantage of peak fall colors for future flights.
AI functionality faces limitations specifically when flying the drone over water.
AI tracking issues arise due to water reflections affecting drone performance.
Manual mode provides better control and recovery options over water.
The challenges faced by the DJI Neo underscore ongoing issues in adapting AI algorithms for diverse environments. Drones often rely heavily on visual processing, which can be disrupted by reflective surfaces like water. Research into improving AI robustness against such factors is crucial, as the functionality directly impacts usability in real-world applications, particularly for leisure or professional use where water encounters are common.
While DJI's drones are generally well-received, the specific issues discussed highlight a significant gap in technology when operating in aquatic environments. Competing technologies may emerge to address such shortcomings, emphasizing the necessity for innovation in AI applications within drone technology. Market demand for multi-environment functionalities might drive future developments in AI algorithms, particularly those capable of overcoming reflection-related challenges.
The drone’s AI lacks effectiveness when tracking subjects over reflective surfaces like water.
High reflective activity creates challenges for the drone's AI in identifying targets.
Engaging manual mode is necessary for safely flying the drone over water when AI tracking fails.
The video discusses the DJI Neo's varying functionalities and challenges in AI-driven operations.
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