Current challenges in soft robotics include sensing and state awareness. Modern soft robotic systems require many more sensors than traditional robots to estimate pose and contact forces. Existing soft sensors include resistive, conductive, optical, and capacitive sensing, with each sensor requiring electronic circuitry and connection to a dedicated line to a data acquisition system, creating a rapidly increasing burden as the number of sensors increases. We demonstrate a network of fiber-based displacement sensors to measure robot state (bend, twist, elongation) and two microfluidic pressure sensors to measure overall and local pressures. These passive sensors transmit information from a soft robot to a nearby display assembly, where a digital camera records displacement and pressure data. We present a configuration in which one camera tracks 11 sensors consisting of nine fiber-based displacement sensors and two microfluidic pressure sensors, eliminating the need for an array of electronic sensors throughout the robot. Finally, we present a Cephalopod-chromatophore-inspired color cell pressure sensor. While these techniques can be used in a variety of soft robot devices, we present fiber and fluid sensing on an elastomeric finger. These techniques are widely suitable for state estimation in the soft robotics field and will allow future progress toward robust, low-cost, real-time control of soft robots. This increased state awareness is necessary for robots to interact with humans, potentially the greatest benefit of the emerging soft robotics field.