Welcome Guest! To enable all features please Login or Register.



Go to last post Go to first unread
#1 Posted : 04 September 2019 12:54:28(UTC)

Rank: Newbie

Groups: Registered
Joined: 08/02/2019(UTC)
Posts: 0
Location: Rome

Basic elements of IoT architecture


Device management

To ensure sufficient functioning of IoT devices, it’s far not enough to install them and let things go their way. There are some procedures required to manage the performance of connected devices (facilitate the interaction between devices, ensure secure data transmission and more):

Device identification to establish the identity of the device to be sure that it’s a genuine device with trusted software transmitting reliable data.
Configuration and control to tune devices according to the purposes of an IoT system. Some parameters need to be written once a device is installed (for example, unique device ID). Other settings might need updates (for example, the time between sending messages with data).
Monitoring and diagnostics to ensure smooth and secure performance of every device in a network and reduce the risk of breakdowns.
Software updates and maintenance to add functionality, fix bugs, address security vulnerabilities.

User management

Alongside with device management, it’s important to provide control over the users having access to an IoT system.

User management involves identifying users, their roles, access levels and ownership in a system. It includes such options as adding and removing users, managing user settings, controlling access of various users to certain information, as well as the permission to perform certain operations within a system, controlling and recording user activities and more.

Security monitoring

Security is one of the top concerns in the internet of things. Connected things produce huge volumes of data, which need to be securely transmitted and protected from cyber-criminals. Another side is that the things connected to the Internet can be entry points for villains. What is more, cyber-criminals can get the access to the “brain” of the whole IoT system and take control of it.

To prevent such problems, it makes sense to log and analyze the commands sent by control applications to things, monitor the actions of users and store all these data in the cloud. With such an approach, it’s possible to address security breaches at the earlies stages and take measures to reduce their influence on an IoT system (for example, block certain commands coming from control applications).

Also, it’s possible to identify the patterns of suspicious behavior, store these samples and compare them with the logs generated by an IoT systems to prevent potential penetrations and minimize their impact on an IoT system.

IoT architecture example – Intelligent lighting

Let’s see how our IoT architecture elements work together by the example of smart yard lighting as a part of a smart home – a bright illustration of how an IoT solution simultaneously contributes to user convenience and energy efficiency. There are various ways a smart lighting system can function, and we’ll cover basic options.


Basic components

Sensors take data from the environment (for example, daylight, sounds, people’s movements). Lamps are equipped with the actuators to switch the light on and off. A data lake stores raw data coming from sensors. A big data warehouse contains the extracted info smart home dwellers’ behavior in various days of the week, energy costs and more.

Manual monitoring and manual control
Users control smart lighting system with a mobile app featuring the map of the yard. With the app users can see which lights are on and off and send commands to the control applications that further transmit them to lamp actuators. Such an app can also show which lamps are about to be out of order.

Data analytics

Analyzing the way users apply smart lighting, their schedules (either provided by users or identified by the smart system) and other info gathered with sensors, data analysts can make and update the algorithms for control applications.

Data analytics also helps in assessing the effectiveness of the IoT system and revealing problems in the way the system works. For example, if a user switches off the light right after a system automatically switches it on and vice versa, there might be gaps in the algorithms, and it’s necessary to address them as soon as possible.

Automatic control’s options and pitfalls

The sensors monitoring natural light send the data about the light to the cloud. When the daylight is not enough (according to previously stated threshold), the control apps send automatic commands to the actuators to switch on the lamps. The rest of the time the lamps are switched off.

However, a lighting system can be “baffled” by the street illumination, lamps from neighboring yards and any other sources. Extraneous light captured by sensors can make the smart system conclude that it’s enough light, and lighting should be switched off. Thus, it makes sense to give the smart system a better understanding of the factors that influence lighting and accumulate these data in the cloud.

When sensors monitor motions and sounds, it’s not enough just to switch on the light when movements or sounds are identified in the yard or switch all the lamps off in the silence. Movements and sounds can be produced, for example, by pets, and cloud applications should distinguish between human voices and movements and those of pets. The same is about the noises coming from the street and neighboring houses and other sounds. To address this issue, it’s possible to store the examples of various sounds in the cloud and compare them with the sounds coming from the sensors.

Machine learning

Intelligent lighting can apply models generated by machine learning, for example, to recognize the patterns of smart home owners’ behavior (leaving home at 8 am, coming back at 7 pm) and accordingly adjust the time when lights are switched on and off (for example, switch the lamps on 5 minutes before they will be needed).

Analyzing users’ behavior in long-time perspective, a smart system can develop advanced behavior. For example, when sensors don’t identify typical movements and voices of home inhabitants, a smart system can “suppose” that smart home dwellers are on a holiday and adjust the behavior: for example, occasionally switch on the lights to give the impression that the house is not empty (for security reasons), but do not keep the lights on all the time to reduce energy consumption.

User management options

To ensure efficient user management, the smart lighting system can be designed for several users with role distribution: for example, owner, inhabitants, guests. In this case, the user with the title “owner” will have full control over the system (including changing the patterns of smart light behavior and monitoring the status of the yard lamps) and priorities in giving commands (when several users give contradicting commands, an owner’s command will be the one control apps execute), while other users will have access to a limited number of the system’s functions. “Inhabitants” will be enabled to switch on and off the lamps with no opportunity to change settings. “Guests” will be able to switch on and off the light in some parts of the house and have no access to controlling the lights, for example, near the garage.

Apart from role distribution, it’s essential to consider ownership (as soon as one system can control over 100 thousand of households, and it’s important that a dweller of a smart home manages the lighting in his yard, and not the one of a neighbor).

Reference https://www.scnsoft.com/...utshell-and-how-it-works
Users browsing this topic
Forum Jump  
You cannot post new topics in this forum.
You cannot reply to topics in this forum.
You cannot delete your posts in this forum.
You cannot edit your posts in this forum.
You cannot create polls in this forum.
You cannot vote in polls in this forum.