Gone are the days of the traditional loom in which an operator feeds the shuttle back and forth, weaving through the fabric threads, methodically checking for flaws and defects. In today's modernised textile industry with multiple spooled feeds, precision mechanised parts and sophisticated computer-programming makes it excessively difficult to conduct effective quality control measures. Under the FAST project, an automated detection system, developed by a host of industrial concerns, now aims at minimising undetected flaws and defects. Based on smart chip technology, and utilising both optical sensors and digital processors, the new inspection system can potentially reduce undetected faults by 70%. Furthermore, this architecture has the potential to perform imaging operations to detect such causes as filtering, edge detection, thresholding and thinning. Further development of the smart chip will see its inclusion with Integrated Vision Camera technologies along with the Hierarchical Neural Network previously developed. Currently, the Near Sensor Image Processing detection system is controlled by low cost computer technology. It results in a direct improvement in both quality measures and time savings and cost reductions at the mending stage in particular as far as silks and jacquard materials are concerned. The FAST system is capable of monitoring multiple looms simultaneously both in a production capacity and in a functional capacity. It therefore allows immediate repair of malfunctioning looms. Its beneficial impacts will be felt in both the textile industry and within the labour force it employs. By improving quality control methods, and supplying advanced loom control equipment, it will contribute directly to the improvement of the overall textile manufacturing industry. By reducing the need for employees in a high-stress and significant position, it will create better job opportunities.