ASIC Design for Industrial Applications

Smart cities aim at improving urban infrastructure efficiency and the life quality for all: inhabitants, visitors, workers and companies. Detecting pollution peaks, smart lighting, intelligent transport systems, smart power grids... they are all deep challenges that are addressed by IoT.

Thanks to cameras and light sensors, smart and connected devices literally observe their environment and monitor the dynamics. This enables them to carry out a wide range of decisional information and automated tasks that are key for ITS: from the smart management of traffic congestions at streetlights to economically and environmentally responsible lighting management in smart buildings, homes, and neighborhoods.

As part of our expertise, we have developed a low-power, low-resolution image sensor ASIC. It is a smart self-contained multi-sensor chip enabling key functionalities for integrated IoT applications where guaranteed low-resolution images are required e.g., for privacy reasons.

With the emergence of industry 4.0, today’s manufacturing networks are operating with an increased risk of cyber threats, and need to be robustly protected. On the other side, the deployment of automation, cobots, and specific autonomous manufacturing tasks increase the risk of accident, and safety is a pillar of autonomous manufacturing.
 
The same is true on a smart city level. Business districts and neighborhoods are made safer and thus more attractive and accessible with surveillance that respects peoples’ privacy by using low-resolution image detection without the option for facial recognition. Safety considerations will in the future also have to include adverse weather events caused by climate change, requiring detection and smart processing of water levels and other parameters, as well as the need for autonomous transportation to connect to the network infrastructure.

As part of our expertise, we have developed an LVDS IP for fast IO communication to read out a fingerprint sensor, analyze the fingerprint, and calculate a fingerprint signature.

Production Infrastructures are becoming increasingly complex. At the same time, with just-in-time production and varying supply chain demands, there is no leeway for extended downtimes. The solution is predictive maintenance: weak points in production lines can be identified in real-time well before actual failure, and maintenance can be scheduled intelligently to avoid particularly busy or otherwise critical periods.

Presto's analog front-end for optoelectronics coupled with an environmental sensor interface is directing playing into cobots in the factory for automation (automatic vision), process control (analog measurements), and preventive maintenance.