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| en:iot-reloaded:iot_systems_architectures [2025/01/06 12:21] – [IoT system architectures] pczekalski | en:iot-reloaded:iot_systems_architectures [2025/05/13 14:45] (current) – pczekalski | ||
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| - | ===== IoT v.s. Wireless | + | ===== IoT vs Wireless |
| People often think of IoT systems as WSN systems (figure {{ref> | People often think of IoT systems as WSN systems (figure {{ref> | ||
| - **Wireless: | - **Wireless: | ||
| - **Self-configuration Typically: | - **Self-configuration Typically: | ||
| - | - **Limited resources: | + | - **Limited resources: |
| <figure Typical_WSN_architecture> | <figure Typical_WSN_architecture> | ||
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| WSN systems, depending on their application and technical solutions, might be split into several groups: | WSN systems, depending on their application and technical solutions, might be split into several groups: | ||
| - | - **Terrestrial WSNs:** They enable | + | - **Terrestrial WSNs** enable |
| - **Underground WSNs:** Usually structured deployment underground with limited communication distances. Expensive deployment and maintenance. Typical application – civil construction. | - **Underground WSNs:** Usually structured deployment underground with limited communication distances. Expensive deployment and maintenance. Typical application – civil construction. | ||
| - **Underwater WSNs:** Nodes are limited in communication distances and bandwidths. Data is collected by manned or unmanned surface water vehicles. Wave energy might be used to recharge batteries. | - **Underwater WSNs:** Nodes are limited in communication distances and bandwidths. Data is collected by manned or unmanned surface water vehicles. Wave energy might be used to recharge batteries. | ||
| - **Mobile WSNs:** In addition to the mentioned functions, Mobile WSNS are capable of self-propelling to relocate or interact with their environment. | - **Mobile WSNs:** In addition to the mentioned functions, Mobile WSNS are capable of self-propelling to relocate or interact with their environment. | ||
| - | - **Multimedia WSNs:** Low-cost | + | - **Multimedia WSNs:** Low-cost noise, sound, image, etc., sense and pre-processing |
| - | ===== Typical | + | ===== Typical |
| Depending on the application and particular functionality, | Depending on the application and particular functionality, | ||
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| - | ===== Difference | + | ===== Difference |
| - | Due to developments in infrastructure and communications technologies, | + | Due to developments in infrastructure and communications technologies, |
| **WSN v.s. IoT challenges: | **WSN v.s. IoT challenges: | ||
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| * Interaction with smart environments – smart appliances, smart cities, smart vehicles. What are the measures of connectivity, | * Interaction with smart environments – smart appliances, smart cities, smart vehicles. What are the measures of connectivity, | ||
| - | ===== IoT system architectures | + | ===== IoT System Architectures |
| IoT is a network of physical things or devices that might include sensors or simple data processing units, complex actuators, and significant hybrid computing power. Today, IoT systems have transitioned from being perceived as sensor networks to smart-networked systems capable of solving complex tasks in mass production, public safety, logistics, medicine and other domains, requiring a broader understanding and acceptance of current technological advancements, | IoT is a network of physical things or devices that might include sensors or simple data processing units, complex actuators, and significant hybrid computing power. Today, IoT systems have transitioned from being perceived as sensor networks to smart-networked systems capable of solving complex tasks in mass production, public safety, logistics, medicine and other domains, requiring a broader understanding and acceptance of current technological advancements, | ||
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| === Fog Computing === | === Fog Computing === | ||
| - | Fog computing (figure {{ref> | + | Fog computing (figure {{ref> |
| Fog computing is a trend that aims to process data near the source. It pushes applications, | Fog computing is a trend that aims to process data near the source. It pushes applications, | ||
| Fog computing enables data analytics and knowledge generation closer to the data source. Furthermore, | Fog computing enables data analytics and knowledge generation closer to the data source. Furthermore, | ||
| - | The recent development of energy-efficient hardware with AI acceleration enters the fog class of the devices, putting fog computing in the middle of the interest of IoT application development and extending new horizons to them. Fog computing is more energy efficient than raw data transfer to the cloud and back, and in the current scale of the IoT devices, the application is meant for the future of the planet Earth. Fog computing usually also has a positive impact on IoT security, e.g., sending pre-processed and depersonalised data to the cloud and providing distributed computing capabilities that are more attack-resistant. | + | The recent development of energy-efficient hardware with AI acceleration enters the fog class of devices, putting fog computing in the middle of the interest of IoT application development and extending new horizons to them. Fog computing is more energy efficient than raw data transfer to the cloud and back, and on the current scale of IoT devices, the application is meant for the future of the planet Earth. Fog computing usually also has a positive impact on IoT security, e.g., sending pre-processed and depersonalised data to the cloud and providing distributed computing capabilities that are more attack-resistant. |
| <figure fog> | <figure fog> | ||
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| === Edge Computing === | === Edge Computing === | ||
| - | Recent developments in hardware, power efficiency, and a better understanding of IoT data nature, including privacy and security, led to solutions where data is processed and pre-processed right to their source in the Edge class devices. Edge data processing on end-node IoT devices is crucial in systems where privacy is essential and sensitive data is not to be sent over the network (e.g. biometric data in a raw form). Moreover, distributed data processing can be considered more energy efficient in some scenarios where, e.g. extensive, power-consuming processing can be performed during green energy availability (figure {{ref> | + | Recent developments in hardware, power efficiency, and a better understanding of IoT data nature, including privacy and security, led to solutions where data is processed and pre-processed right at its source in the Edge class devices. Edge data processing on end-node IoT devices is crucial in systems where privacy is essential and sensitive data is not to be sent over the network (e.g. biometric data in a raw form). Moreover, distributed data processing can be considered more energy efficient in some scenarios where, e.g. extensive, power-consuming processing can be performed during green energy availability (figure {{ref> |
| <figure edge> | <figure edge> | ||
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| * **understanding** – in the case of IoT, it means systems' | * **understanding** – in the case of IoT, it means systems' | ||
| * **reasoning** – involves decision-making according to the understood model and acquired data, | * **reasoning** – involves decision-making according to the understood model and acquired data, | ||
| - | * **learning** – creating new knowledge from the existing, sensed data and elaborated models. | + | * **learning** – creating new knowledge from existing, sensed data and elaborated models. |
| Usually, cognitive IoT systems or C-IoT are expected to add more resilience to the solution. Resilience is a complex term explained differently in different contexts; however, there are standard features for all resilient systems. As a part of their resilience, C-IoT should be capable of self-failure detection and self-healing that minimises or gradually degrades the system' | Usually, cognitive IoT systems or C-IoT are expected to add more resilience to the solution. Resilience is a complex term explained differently in different contexts; however, there are standard features for all resilient systems. As a part of their resilience, C-IoT should be capable of self-failure detection and self-healing that minimises or gradually degrades the system' | ||
| Recent developments in the Fog and Edge class devices and the efficient software leverage cognitive IoT Systems to a new level. | Recent developments in the Fog and Edge class devices and the efficient software leverage cognitive IoT Systems to a new level. | ||
| - | All presented before | + | All IoT System Architectures |
| - | Since market and technology acceptance of mobile devices is still growing, and the amount of produced data from those devices is growing exponentially, | + | Since market and technology acceptance of mobile devices is still growing, and the amount of produced data from those devices is growing exponentially, |
| - | driving forces of the technological advancements of the near future. | + | |
