learning objectives by the end of this lesson you will be able to explain the iot architecture and frameworks describe the iot interoperability as design considerations and discuss industry-aligned use cases iot device architecture there are four layers in the device architecture the base layer consists of iot devices this includes all the components like sensors with the ability to sense compute and connect other devices let's move on to the second layer which is the iot gateway or aggregation layer this layer significantly aggregates data from various sensors these two layers form the definition engine and they set the rules for data aggregation next layer is based on cloud is called processing engine or event processing layer it has numerous algorithms and data processing elements that are ultimately displayed on a dashboard this layer basically processes the data obtained from the sensor layer the last layer is called the application layer or api management layer it acts as an interface between third-party application and infrastructure the entire landscape is supported by device managers and identity and access managers which are useful for security of the architecture iot reference architecture next let's learn about the various layers in iot reference architecture device layer the device layer is the main component where there are various devices like sensors that are interconnected some examples are bluetooth connected via mobile phone and zigbee via zigbee gateway the other devices include the raspberry pi that's connected to the ethernet via wi-fi this is directly connected to the communication layers which are part of the second layer communication layer the communication layer or gateway layer has rest protocols and other application level protocols both layers are tightly coupled and generate enormous amount of data now the bus layer or aggregation layer acts as a message broker it forms a bridge between the data and the communication layer for the sensors this is an important layer for three reasons it supports an http server and or a mqtt broker it aggregates and combines communications via gateway and it bridges and transforms data between different protocols the next layer is the event processing and analytics layer which drives data and provides transformation to the data generated it provides the ability to do event processing the data is stored in the database the client layer is used to create a web-based engine to interact with external apis this can be fed into the api management systems this layer helps create a dashboard and provides a view of the analytics and event processing this layer helps communicate with systems outside the network using machine and machine communication so we've seen the comprehensive iot reference architecture with various components rule engines interfaces and security systems embedded cross-functional architecture is possible using device manager that provides a single platform for remote management the device manager communicates with devices through set protocols device management uses device management agents and is responsible for the remote management of software the identity layer has the capabilities of cyber security including policy control and oauth 2 token instruments other capabilities include identity services xacml pdp and directory of users eg ldap iot reference frameworks there are a lot of frameworks for iot setup but the most common is the iso 30141 and it provides commonly used vocabulary reusable designs and best practices for any developer to design an application it also has many secure application standards that derive the maximum benefit for the organization and reduce the risks iot standardization and design considerations there are a number of iot standards and these are evolving over time some of the key ones are m2m that is a machine to machine service layer that can be embedded in hardware and software to connect devices contiki which is an open source operating system for low-cost low-power iot microcontrollers light os a unix-like operating system for wireless sensor networks random phase multiple access this is a proprietary standard for connecting iot objects the last one is sig fox a proprietary low power low thorough put technology for iot and m2m communications iot interoperability challenges iot maturity comes with several challenges specifically pertaining to interoperability and interfacing the reasons are coexistence of multifarious systems devices sensors equipment etc that interchange location time dependent information in varied data formats languages data models constructs data quality and complex interrelationships multivision system designed by manufacturers over time for varied application domains making formulation of global agreements and commonly accepted specifications very difficult new things that get introduced and that support a new unanticipated structures and protocols existence of low-power devices which need to exchange data over lossy networks and may have minimal likelihood or accessibility for a power recharge in months or years iot design considerations when you choose an iot solution you need to consider several factors like its wireless capability functionality interoperability secure storage immediate boot capacity device categorization bandwidth cryptographic control and power management the design considerations should be a mix of the estimated average of all these components and index to balance the user requirements you also need to set up a dispute resolution mechanism in case of failure in the long run iot device architecture network and cloud there are four stages of integrating the different iot processes stage 1 network things wireless sensors and actuators stage 2 sensor data aggregation systems and analog to digital data conversion stage 3 the appearance of edge i.t systems stage four analysis management and storage of data as these stages are evolving the devices the network and the cloud application must be leveled equally in ecosystem for better stability and security the iot architecture is a combination of things devices platform and sensors with data stage 1 of an iot architecture consists of networked things typically wireless sensors and actuators stage 2 has internet gateways and data acquisition systems that includes sensor data aggregation systems and analog to digital conversion in stage 3 edge it systems perform pre-processing of the data before it moves to the data center or cloud finally in stage 4 data center and cloud is where the data is analyzed managed and stored on traditional backend data center systems fundamentally we need to have a functional scalable available and maintainable architecture if these are not supported then architecture is not useful now let's look at the three architecture areas of iot one the client side iot device layer two operators on the server side iot gateway layer and three a pathway for connecting clients and operators iot platform layer these three layers interface with each other on a data synchronization front and pathway to generate more data from various applications the feasibility of the layers depends on their application let's now differentiate between centralized and decentralized iot architectures the centralized architecture is a hub and is managed from one point whereas the decentralized one is based on the use case they do not help in industrial iot solution the centralized architecture is associated with cloud architectures in which a central hub provides a series of back-end services to smart devices in decentralized architecture there are many scenarios that require autonomous communication between smart devices and an iot topology without the need of essential hub the centralized systems help in event processing and whereas decentralized systems operate more of peer-to-peer messaging the decentralized auditing is one of the essential features that decentralized architecture use case i have smart farming use case smart farming iot design this use case addresses the design formalities using iot iot design is an essential part of the navigational ecosystem smart farming requires precise architecture and components that help bring benefits to the farmers the various factors that determine the iot design are data cost efficiency and product quality the efficiency and durability of the ecosystem help the farmers plan their harvest and sow based on the climatic conditions using the sensors and geospatial location data so be precise any farmer needs to understand the fundamental design that can help run the ecosystem smart farming is useful as it helps the farmer to predict conditions and sow crops with less cost and utilize automation capabilities to have such systems you need to purchase the right hardware which can monitor the accuracy of data and quality of the sensor once you have these systems you can benefit more from farming there are four things you need to integrate for smart farming first is a data engine smart farming should have a robust data processing engine that can act as the brain and handle data processing storage and lead to efficient output the second is hardware you need to ensure that the hardware is durable and easy to maintain hardware self-fixing algorithms is even better the third aspect is mobile access this is possible using a smartphone along with offline or online mobile applications to enable all three processes you need cloud infrastructure with the edge layer this iot system can enable smart farming for any crops in any geographical location let us look at another use case on using sim cards to monitor sugar level in a diabetic patient diabetes management is a recurring concept where the patient has to check the blood sugar at regular intervals in the traditional way he has to go to the physician lab or he has to have his home blood glucose monitoring system iot can help create a system with the blood glucose data will be transmitted remotely via smartphone and a sim embedded in it identifying the necessary and right hardware is one of the crucial steps of creating such a system you need to choose the sensors for your device or create a custom one which fits the glucometer this can be a sim card the next step is to ensure that the quality of your sensors is good and has seamless integration with the system finally make sure that the data monitoring happens in real time with high accuracy now when the hardware landscape of this ecosystem is ready you need to set the software then first it is crucial that you have software with software pair algorithm for service management to enable this process you need cloud infrastructure with edge and finally a smartphone to work with the devices and sensors key takeaways now that you have completed this lesson you should be able to explain iot reference architectures and frameworks describe the iot interop ability and its design considerations and finally discuss industry-aligned use cases hi there if you like this video subscribe to the simply learn youtube channel and click here to watch similar videos to nerd up and get certified click here