EP 02: How Autonomous Drones are Improving Mining Operations
Road to Drone Autonomy Series a 3-part series where we feature Drone Solution Providers (DSPs) from three different geographies from the European subcontinent to highlight the experiences and journey to adopting autonomous drone operations for a variety of use-cases.
Context
The Drones-as-a-Service (DaaS) model has emerged as one of the largest market segments in the drone industry, connecting hardware engineers, automation software developers, and enterprises looking to adopt drones.
However, Drone Solution Providers (DSPs) around the world have encountered several difficulties in executing repeatable UAV missions for data collection, particularly in inaccessible and sometimes dangerous locations. The reliance on operators and visual inspection personnel necessitates significant investment on training, as well as unavailability on demand and other issues.
To scale and perform operations round-the clock, autonomy is essential. Autonomous drones would improve the quality and efficiency of visual data collection, opening up new avenues for scalable commercial operations and applications.
Javier Menéndez
Technical Officer Manager, Cartogalicia
Baisali Ghosh
Marcom Manager, FlytBase
Context
The Drones-as-a-Service (DaaS) model has emerged as one of the largest market segments in the drone industry, connecting hardware engineers, automation software developers, and enterprises looking to adopt drones.
However, Drone Solution Providers (DSPs) around the world have encountered several difficulties in executing repeatable UAV missions for data collection, particularly in inaccessible and sometimes dangerous locations. The reliance on operators and visual inspection personnel necessitates significant investment on training, as well as unavailability on demand and other issues.
To scale and perform operations round-the clock, autonomy is essential. Autonomous drones would improve the quality and efficiency of visual data collection, opening up new avenues for scalable commercial operations and applications.
Javier Menéndez
Technical Officer Manager, Cartogalicia
Baisali Ghosh
Marcom Manager, FlytBase
Context
The Drones-as-a-Service (DaaS) model has emerged as one of the largest market segments in the drone industry, connecting hardware engineers, automation software developers, and enterprises looking to adopt drones.
However, Drone Solution Providers (DSPs) around the world have encountered several difficulties in executing repeatable UAV missions for data collection, particularly in inaccessible and sometimes dangerous locations. The reliance on operators and visual inspection personnel necessitates significant investment on training, as well as unavailability on demand and other issues.
To scale and perform operations round-the clock, autonomy is essential. Autonomous drones would improve the quality and efficiency of visual data collection, opening up new avenues for scalable commercial operations and applications.
Javier Menéndez
Technical Officer Manager, Cartogalicia
Baisali Ghosh
Marcom Manager, FlytBase
What to expect?
The Drones-as-a-Service (DaaS) model has emerged as one of the largest market segments in the drone industry, connecting hardware engineers, automation software developers, and enterprises looking to adopt drones.
However, Drone Solution Providers (DSPs) around the world have encountered several difficulties in executing repeatable UAV missions for data collection, particularly in inaccessible and sometimes dangerous locations. The reliance on operators and visual inspection personnel necessitates significant investment on training, as well as unavailability on demand and other issues.
To scale and perform operations round-the clock, autonomy is essential. Autonomous drones would improve the quality and efficiency of visual data collection, opening up new avenues for scalable commercial operations and applications.
Javier Menéndez
Technical Officer Manager, Cartogalicia
Baisali Ghosh
Marcom Manager, FlytBase
What to expect?
The Drones-as-a-Service (DaaS) model has emerged as one of the largest market segments in the drone industry, connecting hardware engineers, automation software developers, and enterprises looking to adopt drones.
However, Drone Solution Providers (DSPs) around the world have encountered several difficulties in executing repeatable UAV missions for data collection, particularly in inaccessible and sometimes dangerous locations. The reliance on operators and visual inspection personnel necessitates significant investment on training, as well as unavailability on demand and other issues.
To scale and perform operations round-the clock, autonomy is essential. Autonomous drones would improve the quality and efficiency of visual data collection, opening up new avenues for scalable commercial operations and applications.
Javier Menéndez
Technical Officer Manager, Cartogalicia
Baisali Ghosh
Marcom Manager, FlytBase
Context
The Drones-as-a-Service (DaaS) model has emerged as one of the largest market segments in the drone industry, connecting hardware engineers, automation software developers, and enterprises looking to adopt drones.
However, Drone Solution Providers (DSPs) around the world have encountered several difficulties in executing repeatable UAV missions for data collection, particularly in inaccessible and sometimes dangerous locations. The reliance on operators and visual inspection personnel necessitates significant investment on training, as well as unavailability on demand and other issues.
To scale and perform operations round-the clock, autonomy is essential. Autonomous drones would improve the quality and efficiency of visual data collection, opening up new avenues for scalable commercial operations and applications.
Javier Menéndez
Technical Officer Manager, Cartogalicia
Baisali Ghosh
Marcom Manager, FlytBase
