Pest control remains a persistent challenge in Philippine smallholder agriculture, exacerbated by tropical climate conditions and the health risks associated with manual pesticide application. Despite advances in precision agriculture, affordable and locally adaptable automated spraying systems remain limited for smallholder rice farmers. This study developed and evaluated AutoPest, a solar-powered Internet of Things (IoT)-based automated pesticide sprinkler designed to reduce labor demands, minimize pesticide overuse, and improve application accuracy in sustainable farming practices. A descriptive developmental research design was employed, with data collected from 25 rice farmers and 5 IT experts in New Washington, Aklan, Philippines, selected through purposive sampling. Performance was assessed using a validated four-point Likert scale questionnaire across six criteria, and data were analyzed using descriptive statistics (mean, standard deviation). Results indicated that AutoPest performed at a high level in terms of efficiency (M = 3.52), safety (M = 3.64), usability (M = 3.59), and acceptability (M = 3.67), while accuracy (M = 3.40) and reliability (M = 3.45) were rated as moderate. These findings demonstrate that AutoPest is a promising automated solution for sustainable smallholder farming, though further design improvements in spray coverage and system reliability are recommended before broader deployment.