The feasibility of using low-resolution thermal imagers for home security applications is analyzed, taking low cost as the primary consideration. The smallest possible sensor size and resolution are chosen as the operative criteria and derived by simulation, in accordance with the optical constraints of a general home security system and the minimum target feature recognizable using image processing. Lowresolution simulated thermal images were generated by downgrading the high-resolution images captured by an uncooled IR camera, through sampling and modification. Caricatures of human beings and family pets are extracted for recognition using aspect-ratio and neural network methods, which are compared with one another for detection probability. It is demonstrated that highly reliable detection of human beings or pets with a minimal target feature of 8x8 pixels can be obtained using the neural network method. Also, a fire can be detected early using its temporal size variation and higher temperature. Finally, low-cost fabrication of the proposed low-resolution passive infrared imaging system with an uncooled FPA sensor utilizing a fully standard application-specific IC CMOS process is also discussed in detail.