smart systems for managing [25; 26], controlling [27], and optimizing production processes [28; 29; 30]; and real-time object location systems [12; 31; 32] are being implemented. The aforementioned solutions are just a few examples of the known applications of IoT technology. The possibilities of implementing traditional solutions are very wide and mainly depend on the needs of the recipients and the ingenuity of their designers, thus influencing the development of a certain area of the service market. At the same time, it should be noted that services and products where real-time transmission requirements play a key role are still major constraints in the implementation of IoT solutions. The need to design real-time applications for IoT (RTIoT) solutions was recognized more than 10 years ago [33]. The first technologies and standards in this area also began to emerge at that time. Examples include: ITCC (Intel Time Coordinated Computing) [34; 35], TSN (Time Sensitive Network) [36], M2M (Machine to Machine Communication) [37], SaaS (Sensing as a Service) [38], and a multi-layered reference model dedicated to IoE (Internet of Everything) technologies [3]. However, most work to date in the field of RTIoT systems has only been concerned with trying to develop selected elements of the IoT architecture [39] or applications and technologies [40; 41] optimized for the highest possible QoS (Quality of Service). These mostly deal with issues related to real-time transmission and protocols, server applications, or real-time databases. As previously mentioned, there was a need for real-time transmission early in the development of the internet, mainly for the purpose of transmitting multimedia data. The RTP/RSTP [42] or XMPP [43] protocols in use at the time did not allow for the parameters associated with time constraints to be met. It was not until the development of the IEEE 802.1 standard in the form of the TSN solution that some conditions were created for the development of data transmission methods that considered time parameters. However, this standard only defines basic mechanisms for time synchronization, transmission scheduling or resource reservation. It does not specify specific communication protocols or algorithms for scheduling and routing data transmission [44]. In terms of server applications, there is ongoing work on cloud computing. This work focuses on developing real-time cloud services, scheduling tasks according to real-time requirements, and developing web servers that handle requests with time constraints [45; 46; 47]. Real-time databases, on the other hand, define real time as the fastest execution of queries to a database. Examples of such databases are VoltDB [48] and Firebase [49]. Although it is possible to find numerous publications presenting examples of IoT applications running in real time, these solutions are not fully compatible with the concept of a real-time system. Typically, these solutions are highly optimized in terms of data processing and data transmission performance so the time requirements under typical operating conditions are met. However, such solutions do not provide the required QoS level when operating conditions change (e.g., with higher network load). Moreover, providing high performance is often associated with significant costs of computing and communication resources. Additionally, the methodologies of designing RTIoT systems that take cost and QoS optimization into account are unknown. Constraints related to real-time requirements are currently one of the main challenges faced by IoT system research, and they were also the main motivation for the authors of this study to carry out the presented research. The purpose of this work was to identify the problems and needs that exist in the design of RTIoT systems, to identify research directions to solve these problems, and to propose a design methodology that considers the requirements of RTIoT systems.