The predicted growth of urban populations has prompted researchers and administrations to improve services provided to citizens. At the heart of these services are wireless networks of multiple different sensors supported by the Internet of Things. The main purpose of these networks is to provide sufficient information to achieve more intelligent transport, energy supplies, social services, public environments (indoor and outdoor) and security, etc. Two major technological advances would improve such networks in Smart Cities: efficient communication between nodes and a reduction in each node's power consumption. The present paper analyses how event-based sampling techniques can address both challenges. We describe the fundamentals of the triggering mechanisms that characterise Send-on-Delta, Send-on-Area, Send-on-Energy and Send-on-Prediction techniques to restrict the number of transmissions between the sensor node and the supervision or monitoring node without degrading tracking of the sensed variable. At the same time, these aperiodic techniques reduce consumption by sensor node electronic devices. In order to quantify the energy savings, we evaluate the increase achieved in the average lifetime of sensor node batteries. The data provided by Smart City tools in the city of Santander (Spain) were selected to conduct a case study of the main pollutants that determine city air quality: SO2 , NO2 , O3 and PM10 . We conclude that event-based sensing techniques can yield up to 50% savings in sensor node consumption compared to classical periodic sensing techniques
