Widespread access to the internet is offering new possibilities for data collection in surveillance. We explore, in this study, the possibility of using an electronic tool to monitor occurrence of the tick vector of Lyme disease, Ixodes scapularis. The study aimed to compare the capacity for ticks to be identified in web-based submissions of digital images/photographs, to the traditional specimen-based identification method used by the provincial public health laboratory in Quebec, Canada. Forty-one veterinary clinics participated in the study by submitting digital images of ticks collected from pets via a website for image-based identification by an entomologist. The tick specimens were then sent to the provincial public health laboratory to be identified by the ‘gold standard’ method using a microscope. Of the images submitted online, 74·3% (284/382) were considered of high-enough quality to allow identification. The laboratory identified 382 tick specimens from seven different species, with I. scapularis representing 76% of the total submissions. Of the 284 ticks suitable for image-based species identification, 276 (97·2%) were correctly identified (Kappa statistic of 0·92, Z = 15·46, P < 0·001). This study demonstrates that image-based tick identification may be an accurate and useful method of detecting ticks for surveillance when images are of suitable quality.