The proliferation of radio communication systems and the significant advances in enabling device technologies are pa- ving towards Internet-of-Things (IoT) and opening new hori- zons for Smart City applications and its services. Such evo- lution becomes essential in order to enhance quality of ur- ban services, to reduce costs, and to engage citizens more actively. In this context, novel simulation tools are required to prepare the future deployments of large-scale IoT infras- tructure for Smart cities in the best conditions in terms of reliability, energy consumption, and cost. This keynote ses- sion presents the CupCarbon framework: a platform for de- signing smart-city and IoT Wireless Sensor Networks (SCI- WSN). CupCarbon aims to provide following benefits that makes it significant from the other conventional wireless sen- sor network simulators. (1) provides modeling and simulation of radio propagation channel and alpha-stable noise based interferences in more realistic way, (2) takes into account the deployment environment and quantify the uncertainty of simulations, (3) allows the representation of mobile nodes and dynamic environments, (4) allows the behavioural study of a network or networks with large number of nodes in practical environments (city, mountain, etc.). The CupCarbon simulator allows it’s user to design, visu- alize, debug and validate distributed algorithms for moni- toring environmental data collections of wireless sensor net- work. It creates environmental scenarios such as fires, gas, mobiles, and generally within educational and scientific pro- jects. It offers two different simulation environments. First is a multi-agent environment that enables the design of mo- bility scenarios and the generation of events such as fires and gas as well as the simulation of mobile nodes. Second en- vironment represents a discrete event simulation of wireless sensor networks which also takes into account the scenario designed on the basis of the first environment. Interference models based on the impulsive nature of noise and outdoor propagation models are embedded within Cup- Carbon to provide more realistic analysis of WSNs for smart city applications. These models are associated with spatial zones according to the electromagnetic interactions.