## 1 Introduction
The design of mission-critical IoT, unlike traditional mission-critical systems, is very challenging because of the non-deterministic delays of networks. However, it also brings many benefits, as long as the missions are monitored and planned remotely without being on premises. Therefore, in their design, the involvement of stakeholders is more important than that of technical people. The stakeholders of mission-critical applications are the general public who usually lack technical depth, and in order to enable them to tinker with the design and planning of these critical systems, a do-it-yourself (DIY) visual programming language needs to be adopted [20]. The DIY principal has been gaining popularity in recent years. It not only enables the general public to design systems with zero coding but also presents the architecture more robustly and cleanly. Different DIY-based systems are presented in the literature which focus on the ease of the design process and enable non-technical users to design systems without the need to dig deeper into the technical world [20]. As described, mission-critical systems require a very clear and robust picture of the design and architecture due to the severity of its consequences. Therefore, the DIY paradigm suits best for such systems. In this paper, we present a multi-platform architecture which uses a DIY approach to design and monitor missions in an autonomous and optimal way. The architecture employs autonomous task-object mapping and deployment. The tasks are presented with the top-most virtual objects having a suggestion index higher than others for autonomous mapping. The approach is adopted because the task and object will form a small microservice which can be deployed on physical hardware. The size of the data is very crucial in mission-critical systems due to the stringent requirements of time and performance. Therefore, it is preferred to deploy a small message more often than a big chunk of the message. A case study was performed on the proposed architecture which intelligently detects smoke in a smart building and prevents the hazard of fire. The contributions of this paper include  
* The design and implement a multi-platform architecture for mission planning and analysis based on the DIY paradigm to encourage the involvement of non-technical people in mission design;
* The proposal of an intelligent task-object mapping model for microservice deployment to decrease message size and improve efficiency;
* The implementation of a case study regarding the the proposed architecture to test its effectiveness. The rest of the paper is organized as follows. Section 2 presents related work and outlines the relevant research in MC-IoT and DIY-based IoT applications. Section 3 exhibits the proposed system model and describes its various components. Section 4 portrays the design in terms of mission-planning and interaction models. Section 5 discusses the implementation environment and outlines the tools and technologies being used in this work. Section 6 presents a case study involving smoke detection mission planning on the proposed architecture and illustrates the execution flow of the system. Section 7 evaluates the performance of the system with state-of-the-art methods and discusses its significance. Section 8 concludes the paper and identifies future directions of this work.