Falconers offers development services focusing on next-generation remote sensing AI and hardware.
Our vision is to decrease the computational energy load by optimizing the system chain from sensors to AI algorithms/hardware development — a positive impact to business and the environment.
When building autonomous devices or ISTAR systems, which require sensor dataprocessing, machine learning and AI, there is always a challenge of computational cost. Depending on the use-case this can be power consumption limits in Edge devices, hardware constraints for device geometry/mass or physical limits of off-the-shelf computational components.
The key to ensuring sensing system reliability in Edge systems and RF-denied environments is optimized hardware. The least energy consuming and highest performance systems can be achieved through joint R&D of both hardware and software. We have experience developing hardware for ground as well as space payload carriers.
Optical sensing has made a decisive leap forward, giving machines with novel sensors and intelligence the capacity to detect and assess what would be left unseen for the human:
- subtle or fast movements
- complex patterns
- traces left in the environment
- camouflaged objects
Our AI and machine vision toolset can be tuned to autonomously observe, detect and track situational developments of areas/objects of interest.This gathered data can be then visualized or observed as historical data or in real-time.
Analyzing sensor data on the Edge is becoming the norm as data volumes increase exponentially. Eliminating energy waste can go a long way for longer battery cycles, preventing unwanted heat in electronics and system reliance longevity. If we can run AI onboard satellites, we can help Your device decrease energy budgets.
Higher efficiency sensor-AI combinations can reduce the mass, volume and cost of devices with potentially having a positive “snowball effect” on the entire system.This translates to more cost-efficient and lighter bill-of-materials.
Optimising the real-time data processing can help reach higher goals: beit faster reaction speeds, increase in range or accuracy. Former bottlenecks can translate to competitive advantages