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| + | ====== IoT Design Methodologies ====== | ||
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| + | IoT systems are networked cyber-physical systems (CPS) and include components from three main domains: the hardware, primarily electromechanical devices; software, mostly microcontroller-specific process control software; and communication infrastructure. To develop an IoT solution, all aspects of these three domains must be designed in great synergy. When looking at the component level, the main building block of the IoT system is a node. The node is usually a microcontroller-based device dedicated to performing a specific task. The most common task is to perform measurements from the environment, | ||
| + | Today, CPS is created by expanding mechatronic systems with additional inputs and outputs and coupling them to the IoT. In principle, the IoT system is similar to classical smart systems, e.g., robots or mechatronic systems. These systems can be decomposed into three interconnected domains: process control by software, mechanical movements, and sensing of physical parameters from the system' | ||
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| + | <figure smartsystem> | ||
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| + | The IoT system has a similar purpose to general smart systems. The main difference is that the IoT system is a distributed solution of smart functions using the internet infrastructure. Similar functionality is decomposed into smaller devices acting as a single functioning device rather than a complex system. Nevertheless, | ||
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| + | <figure smartiotsystem> | ||
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| + | Even if the IoT system has a different component architecture from a regular mechatronic system, the development methodologies can be easily adapted from the domains of mechatronic systems and software system design. IoT systems have their specifics, but at the conceptual level, they are like any other smart software-intensive system. Thus, the methodologies are not IoT-specific but combinations and adaptions from related domains. | ||
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| + | === Product development process === | ||
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| + | The product development process is a well-established domain with many different concepts. Over time, as the software part is increasing in today' | ||
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| + | The classical product design process starts with requirement analysis, followed by conceptual design. When the design candidate is selected, the detailed design stage develops domain-specific solutions like mechanical, electrical, software, etc. The next stage is integrating domain-specific design results into one product and validating the solution. In addition, the product design process must deal with manufacturing preparation, | ||
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| + | <figure productdesign> | ||
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| + | === V-model === | ||
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| + | IoT systems are a combination of mechatronic and distributed software systems. Therefore, design methodologies from these domains are most relevant for IoT systems. For example, the well-known V-model (figure {{ref> | ||
| + | )). This guideline adopts the V-model as a macro-cycle process. The V-model is in line with general product design stages but emphasises the verification and validation through the whole development process. The execution of processes happens sequentially, | ||
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| + | <figure v-model> | ||
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| + | The new product development starts with customer input or other motivation, e.g., a business case, which must be carefully analysed and specified in a structured way. Requirements are not always clearly defined, and putting effort into proper requirement engineering pays off to save significantly from later design stages. It is not good practice to start designing a new system or solution when requirements are not adequately defined. At the same time, rarely all information is available initially, and requirements may be refined or even changed during the design process. Nevertheless, | ||
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| + | The second design stage is system architecture and design, which is dedicated to developing concepts for the whole system. Concept development and evaluation are decomposed into several sub-steps and procedures. For example, the development of different concept candidates, the assessment of concept candidates, and the selection of the best concept solution for further development. Once the concept solution is selected and validated with requirements, | ||
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| + | The whole process may be repeated as often as necessary, depending on the final system' | ||
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| + | === Challenges === | ||
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| + | When designing an IoT system, there are common design challenges, as in any other system engineering project, but also a few IoT-specific aspects. The engineering team must deal with difficulties similar to those of mechatronic and software system design. Some relevant vital elements to address when designing and deploying a new IoT system: | ||
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| + | * New IoT systems often require organisational and working culture changes, which are usually underestimated. Changing workers' | ||
| + | * Due to their complexity and dependence on several existing systems, IoT projects tend to take much longer to implement than anticipated. | ||
| + | * IoT systems are multi-domain solutions and thus require engineering skills from very different fields, some of which might not be available, such as microcontroller programming, | ||
| + | * Interconnectivity issues can be critical as the IoT system components must be able to communicate with each other, but many protocols, network architectures, | ||
| + | * Data security is often underestimated. IoT systems are not standalone but, in most cases, interconnected through the public internet. Implementing cybersecurity is very challenging because the overall system security is defined by its weakest segment. | ||
| + | * Scalability and dealing with legacy equipment. IoT systems often update old heavy machinery in the industry and combine old and new technologies. This might be more challenging than expected and, in some cases, extremely costly to eliminate all interfacing issues. | ||
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| + | <WRAP excludefrompdf> | ||
| + | The following chapters contain more details: | ||
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| + | </ | ||