Machine Learning Techniques and Analytics for Cloud Security. Группа авторов

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Figure 4.1 IoT-based smart home automation system.

      First, we will make an account on the Particle.io. Then, particle agent will be installed with the Raspberry Pi of the embedded system so that interface can be made with particle cloud. This is background software which is able to interact with the Raspberry pi through GPIO pin. Here, we can add new devices as well as create mesh networks, integrated with IFTTT, Microsoft Azure, and web IDE. A block diagram is presented below.

In Figure 4.1, household appliances (fan, light, TV, AC, etc.) represent as target devices which connect with IoT devices or smart sensors which embedded with code. When this IoT device connects with mobile network, it can directly attach with Google API through Google Cloud Console. Using this mobile network, every application of smart phone which acts as tune device can connect with IoT device and can use every module or technique of Google Cloud Console.

      Voice-operated room switching control system is the smarter version of the remote-controlled switching system. As titled, these systems are controlled over voice commands over the internet, thus providing you with no bound for the control. Home is a place where people incline to at the day end. After a long tiring day when people return exhausted, they may find it tough to move around the corner of the room where the switch board for the room appliance control is situated at the convenient locations, closer to the sitting or bed arrangement. It is also difficult for a person to locate the switch board of the staircase, or the room main entrance in the dark. So, if a small technology helps them to switch their room light and fan or other electrical appliances of low wattage or read out the news to them, with a single voice command through their smart phone or table or the control dock settled in their room, it will enhance the comfort experience to next level.

Earlier days, millionaires used to keep housekeepers and other sorts of human assistance for easing up their day. But, for the common man in the society, they were not eligible to taste the crunch of that facility. Even today, when technology is so close by, only established and wealthy people in this contemporary civilization are benefited with these new technologies of elegant house, as these devices are still too expensive. Since everyone in this society are not so wealthy enough to afford smart home kit, thus the need for these in expensive smart kits keeps growing.

      4.5 Motivation of the Project

      This project proposes one very low-priced economical system, where Google Assistant technology (provided by Google to all their OS, and if necessary, it can be downloaded to other smart phone makers too like IOS by Apple) is utilized: the IFTTT server and application, The Blynk application, and Google Cloud Console. In the hardware part, The NodeMCU 8266 micro-controller acts as the major communicator as it receives and sends data to our apps and server, along with a relay board of 4/8 channel, whose regulatory voltage is 5 V and has the capability for handling 10-A current through it. We use our natural language to give command to our Google Assistance and receive data on our Blynk app. We have hereby segregated the total manuscript into two parts: at first, the device, and second, the control unit.

      4.6 Smart Informative and Command Accepting Interface

      Passive Intelligence (PI) is a very important aspect in today’s world and makes a paradigm shift in view of industry initiatives for realizing smart environments. Everyday’s smart devices like smart bag, smart watch, and smart wallet provide that required heterogeneous intelligent interfaces along with other natural devices, and these together makes a complex computing scenario, which, thereafter, generates the vision of PI. The environment becomes respondent to each individual, and therefore, anyone can interact with the surrounding with 1:1 basis. Therefore, user-empowered smart environment can be generated using PI, which provides the required support to human for various interactions.

      In this connection, it should be mentioned that the environment, interfaced with PI, may be the home (comfortable) or a distributed one. For the said purpose, different smart technologies are considered as per the demand. All these technologies are integrated with the environment, for the purpose of sensing and data processing. Networking is also an important phase of this integration in order to provide remote service and also of digital materials. The actual question comes to the embedding of all these smart devices, and here lies the real challenge of PI.

PI can be obtained at the home comfort when proper key technological fruits are perfectly blended with virus smart interfaces (programmable). For the purpose, several smart devices and appliances are invoked, and anyone can be considered as an interface with the real world. In this particular work, authors have tried and successfully implemented a mirror interface with proper incorporation of smart informative system, precisely to get smart home environment. This is depicted in Figure 4.2, embedded with Google Cloud Console. The console has an interface with API controller.

Figure 4.2 Command accepting interface.

The major objective of making a PI at the home is originated from the safety and security concern, associated with efficiency of the system along with convenience. Precisely, elderly people and people with physical disabilities required better attention, when other family members are absent. PI greatly influences not only home automation systems, but also socialization, communication, entertainment, refreshment, proper rest, and various physical activities like sports, working, online learning through MOOCs or in general YouTube videos.

      Another aspect that will engage their footstep with these PI modules will be digital marketing. Henceforth, proper architecture should be considered for convenient and user-friendly PI design where both the technological advancement should be clubbed with home comfort and convenient for the residents.

      4.7 Data Flow Diagram

The workflow for the proposed work can be explained using the dataflow diagram described in Figure 4.3. A bidirectional network is established between mosquito server and IoT controller where data is continuously flowing and periodic update is taking place. The mosquito server is fed through IFTTT, whereas all the applets (including triggering applet) are given similar instructions by the same. Google Cloud Console is the heart of this total workflow, which always dynamically interacts with command interface. It also makes a bidirectional communication with IFTTT, console APIs, and search console. Console APIs receives and also sends commands to command APIs. Web results are retrieved from the search console. The transfer of data and different messages are schematically represented in the diagram given below (Figure 4.2).

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