Prospera, a company founded about 2 years ago by a team of computer scientists and agronomists, has built some very interesting technology that centers around monitoring crop growth, in order to optimize it. While farmers have long had some data like weather readings and low resolution satellite images available to them, it turns out not to be enough. And even if it were, weather data from a government weather station which might be 30km away from the actual growing area doesn't deliver the "hyper-local" climate data that is crucial.
When you grow in volume, though, the geographic dispersal of your farmland makes it difficult to go around and collect that data manually and the rural settings for that farmland make the electrical and network connectivity, that had been necessary to collect that data, hard to come by.
But now low-cost sensors can obtain temperature and humidity data; and low-cost cameras can measure light/radiation and gather valuable images. The devices can communicate over WiFi or 3G mobile data technology and can often run on solar power. This approach has been making technology with great efficacy in indoor agriculture, increasingly applicable in outdoor settings too.
Beyond predictive applications, there are prescriptive applications too. Computer vision/imaging has serious applicability in this domain, as the capture of images combined with pattern recognition technology can help detect crop disease and, on an automated basis, dispatch personnel to address it. It can also help alert farmers to where they need to prune and harvest. So not only is the data collection made more economical, but the methodical analysis of the collected data, and the dispatch of responsive action, is made more feasible and economical as well.