The ever-growing nature of the Internet-of-Things (IoT) and related application domains (Smart home, Smart buildings, etc.) with numerous objects and configurations require more and more autonomy and coordination. Multi-agent systems are a suitable paradigm to model and develop applications and infrastructure to implement such IoT environments. Within the multi-agent techniques, distributed constraint reasoning is a relevant approach to model complex problems and decentralize decisions in a coordinated way. The Tutorial on Distributed Constraint Optimization for the Internet-of-Things proposes to review some DCOP solution methods relevant for the IoT context, to model a real smart home case study, and finally to program and deploy DCOP solutions methods on a real IoT environment composed of Raspberry Pis.