UAVs with precision landing capabilities to rule the roost: Are AI firms ready for the challenge?

The popularity of Unmanned Aerial Vehicles (UAVs)is not hidden from anyone. Many industries are benefiting from this technology and performing difficult activities with the utmost ease.

The latest versions of UAVs are remarkably changing the fortunes of certain sectors, backed by features like precision landing. Such capabilities are the key to perform critical missions across unfavourable environments.  

Recently, UAVs with precision landing capabilities have been attracting many enterprises and advancing into broader verticals. They are able to carry out tasks with great efficiency without harming other devices, leading to an increased lifespan.

Precision landing has become an essential part of any significant task performed by the UAVs and pin-point accuracy is the most celebrated capability of these devices.

At this juncture, it is equally important for the AI firms to work for the integration of such technologies in the UAVs to stay relevant in the market. Soon, the acceptance of these devices may solely depend on the excellence of integrated technologies.

For instance, Internest, a Paris-based deep tech start-up, has developed a technology that guides UAVs to precise landings on fixed or mobile targets, even in harsh weather conditions. Such technologies can improve the safety of UAVsand assist various enterprises in achieving their objectives in a seamless manner.

Recently, Internest was funded by the global investment firm Boundary Holding, led by Rajat Khare.The firm is now planning to expand its customer base and partnership across various sectors. 

It is no secret that the importance of UAVs with precision landing cannot be undermined, especially when the safety of people, livestock and infrastructure comes into play. The only thing that remains to be seen is whether AI firms can innovate further to combat the possible challenges that may restrict the scope of such technologies with a small margin of error.

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