The digitalization of agriculture is on the rise, and while the dairy industry is not considered a leader in digitalization, more and more technologies have been developed in recent years. In particular, monitoring the health of dairy cows is becoming increasingly digital with Internet of Things (IoT) technologies. IoT-based sensors can potentially support efficient dairy production while enabling better animal welfare. Against this background, the question of technology acceptance among dairy farmers is becoming increasingly important. It is evident that acceptance, especially in the area of IoT-based dairy sensors, has only been sporadically researched, with behavioral factors rarely considered. Acceptance research has predominantly focused on a technological perspective or has been limited to operational and socio-demographic factors, thus failing to capture the entire acceptance process. Based on this, the aim of the paper is to identify prevailing acceptance barriers and examine whether cognitive and affective influencing factors, combined into a single behavioral model, can explain the acceptance, and therewith precondition for adoption, of IoT-based animal sensors. For this purpose, an online survey was conducted among 212 German dairy farmers. The analysis included a partial least squares estimation of the behavioral model. The results show that acceptance barriers differ between users and non-users of IoT-based sensors. However, both groups consider high investment costs as the most important barrier. Furthermore, the results indicate that both cognitive factors and positive anticipated emotions influence acceptance decisions. Additionally, the main determinants of the theory of planned behavior, namely attitude and behavioral control, have a positive influence on the desire to use IoT-based animal sensors. Ultimately, this has a positive impact on the acceptance. The results emphasise that, in addition to the technical requirements and cognitive attitudes, emotional factors are relevant for the acceptance of IoT-based animal sensors among dairy farmers. These findings are important for manufacturers, policy and agricultural and digital associations.