Detection of transiting exoplanets requires high precision photometry, at the percent level for giant planets and at the 1e-5 level for detection of Earth-like rocky planets. Space provides an ideally stable - but costly - environment for high precision photometry. Achieving high precision photometry on a large number of sources from the ground is scientifically valuable, but also very challenging, due to multiple sources of errors. These errors can be greatly reduced if a large number of small wide field telescopes is used with an adequate data analysis algorithm, and the recent availability of low cost high performance digital single lens reflex (DSLR) cameras thus provides an interesting opportunity for exoplanet transit detection. We have recently assembled a prototype DSLR-based robotic imaging system for astronomy, showing that robotic high imaging quality units can be build at a small cost (under $10000 per deg2m2 of etendue), allowing multiple units to be built and operated. We demonstrate that a newly developed data reduction algorithm can overcome detector sampling and color issues, and allow precision photometry with these systems, approaching the limit set by photon noise and scintillation noise - which can both average as the inverse square root of etendue. We conclude that for identification of a large number of exoplanets, a ground-based distributed system consisting of a large number of DSLR-based units is a scientifically valuable cost-effective approach.