Studies have shown that drivers often spend over 20 min cruising for parking in city centers, accounting for as much as 30% of the traffic congestion. In response, cities like San Francisco have deployed systems capable of providing drivers real-time parking availability information. However, such systems rely on specialized infrastructure whose installation and maintenance costs in the tens of millions of dollars, unaffordable for many cities. We present SmartPark, a system for real-time parking information that relaxes the requirement for specialized infrastructure, relying instead on the smartphone’s sensors and the ubiquitous Wi-Fi and cellular infrastructure. To accomplish this, SmartPark addresses two major challenges, under the constraint of minimum impact on battery life: transportation mode detection and location matching. To minimize initial deployment cost and risk, SmartPark introduces an analytical approach for estimating parking availability even when only a small fraction of users adopt the application. We evaluate SmartPark using simulations and in the wild. Simulation results show that SmartPark, benefiting from as little as 20% adoption rate, can estimate parking availability with accuracy above 90%. Experimental results with the help of 12 volunteers show that SmartPark detects unparking events 97% of the time while triggering zero false positives.