Objective: To establish and implement a smartphone-based school syndromic surveillance system, and to provide references for school communicable disease control and prevention. Methods: A smartphone-based school syndromic surveillance system was constructed and applied. A list of seven symptoms including fever, cough, vomit, diarrhea, rash, red eye and parotid swelling was classified as targeted indicators. Spatio-temporal permutation scanning was applied to automatic early warning. Results: A total of 1 973 school joined the syndromic surveillance system. System usage rate was 54.13%, no significant differences were found among different types of schools(χ2=1.58, P=0.67), whereas significant differences were observed among counties（χ2=726.78, P<0.01). Totally, 852 036 pieces of symptoms data were reported during September 2018 to March 2019, the primary symptoms included cough (35.17%) and fever (21.11%). Time trends in different symptoms varied with time, with fever and cough highest in January, vomit and diarrhea in November. Thirteen pieces of early warning were confirmed as school communicable diseases by field investigation, the average number of the infected students were four. Conclusion The smartphone-based school syndromic surveillance system is generally acceptable. Characteristic seasonal distributions of school communicable diseases are reflected accurately by surveillance system which plays an active role in prevention and control of school communicable diseases.