Networks of remote sensors are becoming more common as technology improves and costs decline. In the past, a remote sensor was usually a device that collected data to be retrieved at a later time by some other mechanism. This collected data were usually processed well after the fact at a computer greatly removed from the in situ sensing location. This has begun to change as sensor technology, on-board processing, and network communication capabilities have increased and their prices have dropped. There has been an explosion in the number of sensors and sensing devices, not just around the world, but literally throughout the solar system. These sensors are not only becoming vastly more sophisticated, accurate, and detailed in the data they gather but they are also becoming cheaper, lighter, and smaller. At the same time, engineers have developed improved methods to embed computing systems, memory, storage, and communication capabilities into the platforms that host these sensors. Now, it is not unusual to see large networks of sensors working in cooperation with one another. Nor does it seem strange to see the autonomous operation of sensorbased systems, from space-based satellites to smart vacuum cleaners that keep our homes clean and robotic toys that help to entertain and educate our children. But access to sensor data and computing power is only part of the story. For all the power of these systems, there are still substantial limits to what they can accomplish. These include the well-known limits to current Artificial Intelligence capabilities and our limited ability to program the abstract concepts, goals, and improvisation needed for fully autonomous systems. But it also includes much more basic engineering problems such as lack of adequate power, communications bandwidth, and memory, as well as problems with the geolocation and real-time georeferencing required to integrate data from multiple sensors to be used together.