Green Internet of Things and Machine Learning. Группа авторов
to the required services, this stored data is analyzed further and specific operations are performed. There can be various sensors such as temperature sensors, humidity sensors, mobile phones, and wearable sensing devices. Specific sensors are used as per the required service. Hence, sensing is categorized into environmental, biometric, biological, audible or visual, or all the above.
1.8.3 Communication Technologies
Communication technologies are used to connect various components to provide specific services. It uses either wide area network (WAN) communications or Wi-Fi (wireless LAN-based communications), Bluetooth, Z-wave, Near Field Communication (NFC), LTE Advanced, Wi-Fi, ultra wide bandwidth (UWB), IEEE 802.15.4, etc., which are the protocols used by IoT for communication [29].
1.8.4 Computation
Computation is the stage which is performed by the various hardware processing units such as microprocessors, microcontrollers, field programmable gate arrays (FPGAs), system on chips (SoCs), and software applications. To perform the computation, various hardware platforms such as Raspberry PI, Arduino, Intel Galileo, UDOO, Friendly ARM, and Gadgeteer are available, and many software platforms like LiteOS, TinyOS, and Riot OS are used. The important computational component of IoT is the Cloud platform. Since cloud platform has the high capability of computation in order to extract the valuable information from the stored data. Now, the transmission of this stored data takes place to a cloud-based service where other information that arrives from the IoT device is collected along with the cloud-based data in order to yield vital information to the end-user [30]. The data is gathered from the internet and other similar devices connected to the IoT. A process called “Data Processing” is required to extract vital information from the data.
1.8.5 Services
Services of IoT are broadly divided into below classes:
• Identity-related services
• Information aggregation services
• Collaborative-aware services
• Global services
Identity-related services are the foundation for all other services because identification of the object is the primary step for translating the real-world objects to the virtual world.
As the name describes, information aggregation service is used to accumulate the data from various sources. This data is then summarized and processed in order to gain fruitful results. This analyzed information is nowadays helping in making decisions and predictions. Global services denote the services provided to anyone on the demand, anywhere and anytime.
1.8.6 Semantic
Semantic is the name of task where knowledge is extracted intelligently from the mass of data to yield the demanded services. This is done by discovering resources, utilization of resources, modeling information, recognition, and analyzing data. Web ontology language (OWL), efficient XML interchange (EXI), resource description framework (RDF), etc., are the most common semantic technologies.
Figure 1.6 Life cycle of Green IoT.
1.9 Life Cycle of Green IoT
There is huge growth in IoT and its components in upcoming time. Therefore, it is needed to mitigate the number of resources to implement the logic and the reduction of energy as well to keep the things working for longer time. G-IoT relies on the optimum energy consumption.
For the smooth functioning of smart world, IoT should consume less energy and should reduce the green house effects at the same time. It has to focus on to mitigate the emission of CO2 from the devices and sensors [31].
Figure 1.6 represents the life cycle of G-IoT. It has four phases; they are green design, green production, green utilization, and green disposal/ recycle. Here, green disposal means the disposal should be in such a way that there should be no adverse effect on environment. Figure 1.6 depicts the life cycle of G-IoT.
1.10 Applications
In this section, we will discuss the various application based on G-IoT. Figure 1.7 depicts some applications, those that are based on G-IoT.
1.10.1 Industrial Automation
1.10.1.1 Machine to Machine Communications
Automation can be achieved through RFID tags. Without any sort of human intervention, direct communication is made by RFID to the robot [32].
1.10.1.2 Plant Monitoring
IoT helped to the industry for monitoring the various parameters of any plant like temperature, machine faults, and air pollution.
1.10.2 Healthcare
1.10.2.1 Real-Time Tracking
It helps in the monitoring of the patients and tracking of medical equipment.
It also helps in the tracking of the medical instruments in order not to be left in the body of the patient during surgery.
Figure 1.7 Green IoT–based applications.
1.10.2.2 Identification
IoT helps is the identification by coherent tracking methods. RFID-based identification is the easiest way to do it. It provides quick retrieval of patient information and finding the current location of the patient in the hospital. This also helps to reduce the blunder rate of patient incidents like overdose, wrong drug, infant identification (to prevent mismatching), etc., to a great extent by the constant monitoring of the patient information [33].
1.10.2.3 Smart Data Collection
It aids to reduce the processing time in every section either it is related to auditing, searching, or analysis. It also helps in reducing the cost. It provides automated care.
1.10.2.4 Smart Sensing
Various sensors can be used to access the real-time health of patient within seconds.
1.10.3 Environment Monitoring
It helps in monitoring the various changes happening in the environment whether it is temporal, organism, physical, or spatial made by human or nature itself.
1.10.3.1 Agriculture
It measures the water level, this way it helps in suggesting the suitable crop to be grown. It helps in saving of the water by sensing the humidity of the soil. Only required amount of water is supplied then. It prevents forest fires also.