This work documents the development of an aerial environmental monitoring platform based on a paramotor, dubbed robofoil. Significant advantages are achieved in safety, durability, ease of use and flexibility by employing an inflated wing. The aircraft is easy to fly, has near vertical ascent into wind and an intrinsic fail-safe. The ability to control the wing angle of attack and interchange wings according to weather or mission requirements makes this platform truly flexible. With an onboard autopilot and manual override, the vehicle is intuitive to fly and has a short learning curve for the user. With flight speeds ranging from 0 to 40 knots, the vehicle is well-suited to targeted surveillance as well as being resilient to gusty conditions. With a high payload capability, the platform can carry fuel for flights in excess of an hour in the current version. We have established that it is possible to use genetic programming, a machine learning technique, to evolve application-specific systems purely through training. Our eventual aim is for the design, construction details and software used for robofoil to be made fully open