Mosquitoes are recognized as the “world’s deadliest animal” according to the U.S. Centers for Disease Control and Prevention, posing as the leading global health threat, causing more fatalities than any other animal. Addressing this prevalent issue requires enhancing public awareness and strengthening mosquito control measures worldwide. Traditional mosquito surveillance and control methods, such as hand landing catch and natural repellents, are often time-consuming, costly, and lack scalability. In contrast, the widespread availability of mobile devices equipped with high-resolution cameras presents a unique method to approach mosquito monitoring. To leverage this potential, the Global Mosquito Observations Dashboard (GMOD) was developed as a free, public platform to improve the detection and monitoring of invasive and vector mosquitoes. GMOD is an interactive web-based application that collects and displays real-time mosquito observations and habitat data generated globally by citizen scientists. By integrating data from four data streams, the platform enables comprehensive visualization of mosquito population trends and geographic distributions worldwide. Furthermore, GMOD acts as an educational resource that highly promotes global data sharing and collaboration in mosquito management. With continuous data collection, GMOD has provided valuable and actionable insight into the distribution, abundance, and prevalence of mosquito species globally. This research aims to leverage the free platform to actively engage citizen scientists in community-based surveillance efforts, thereby expanding the global monitoring of mosquitoes. As GMOD continues to evolve, the integration of artificial intelligence for species identification holds significant promise to enhance public health initiatives in reducing mosquito-borne diseases, particularly in regions where traditional surveillance methods face challenges.