## 1 Introduction  
Wireless sensor networks (WSN) are employed in a wide range of applications and application domains, and are the subject of considerable research efforts and technological advances to expand their applicability. WSNs were among the enabling technologies of the Internet of Things (IoT) paradigm since it was coined more than 15 years ago [1], and consolidated and expanded their application domains as the IoT paradigm evolved. However, the spread of WSN-based solutions is still limited by several factors, such as technical complexity, perceived reduced reliability and overall cost. The development of efficient WSN applications requires different and complementary views, but competency separation between the typical stakeholders and the engineering disciplines concurring in the WSN domain is not yet mature, which leads to significant inefficiencies. For instance, WSN design and planning can be effort- and risk-intensive, because they require detailed consideration of connectivity, coverage, cost, network longevity, and service quality. In addition, predicting WSN performance before its real deployment is very challenging, which leads to costly trial-and-error procedures. The aim of the ARTEMIS-JU funded project \"WSN Deployment, Planning, and Commissioning & Maintenance\" (WSN-DPCM) presented in this article was to build an integrated platform to support the system integrators to design, develop, test, deploy and maintain WSN applications. The project acknowledged from the beginning that the technical work of system integrators relies heavily on existing hardware and software components and should focus on application-specific parts, as shown in Figure 1.  
Figure 1: WSN-DPCM toolset helps system integrators to focus on customer requirements by hiding most structural and implementation details of WSN platform components. Thus the primary design objectives of the WSN-DPCM platform were:  
* A modular design with components that perform well-defined tasks and communicate through well-defined interfaces and data models, in order to simplify the maintenance and evolution of the platform in line with the fast evolution pace of WSN research and technology;
* To be accessible to application domain experts while allowing experienced developers to optimize the designs as much as possible;
* To reuse open or closed source IP blocks in order to increase the reliability of WSN projects, to reduce the development effort, and to foster commercial exploitation of the platform;
* To allow the developers to focus on application-specific requirements and implementation of the WSN application by reducing the effort needed to select and adapt the existing components to the application, as well as to reduce the effort to plan, commission, troubleshoot and maintain the WSN during its lifetime. In order to meet these aims, the WSN-DPCM platform includes several useful capabilities, such as radio frequency (RF) simulation, network simulation with hardware-in-the-loop (HiL) capabilities, topology optimization, automatic software synthesis, monitoring, debugging, as described in the rest of the article. The effectiveness of the WSN-DPCM toolset is tested in two case studies in different domains. The first is a WSN-based system to monitor the occupancy state of parking lots, of which a prototype has been tested in the parking of the Universidad Politecnica de Madrid (UPM), Spain [2; 3]. The second case study is a WSN-based solution for monitoring air concentration of harmful gases near an industrial site, of which a prototype has been tested at the INTECS premises near Pisa, Italy [4; 5]. Note that both case studies refer to outdoor deployment scenarios. In fact, the proposed toolkit is primarily intended for outdoor WSN applications especially because the ray tracing-based RF simulation is effective to simulate outdoor electromagnetic field propagation. For indoor environments a simple heuristic path loss one-slope model may be used, but with significantly lower prediction accuracy [6].