Green Internet of Things and Machine Learning

Online computational advertisement is the new concept in this scientific era. It is different from classical or traditional advertisement process. Computational advertisement is based on best match of the users. It is reached to the relevant user in digital format or online mode by using various ML techniques, and those are based on recommendation system, text analysis, information retrieval, classification, modeling, and optimization techniques. Within short span and in cost-effective way, it targets the number of relevant person [18].

Sentiment analysis is different from the text analysis. Text analysis is focused to retrieve the facts and information but not be able to find the customer’s sentiments which lead to misunderstand the customers need. This misunderstanding may be loss of the valuable information. Hence, sentiment analysis is important to find the product’s review either a positive or negative. Sentiment categorization used in movie reviews, recommendation systems, and business intelligence applications [18].

Traffic forecasting system is the real-time prediction of the traffic on the road. Day by day, numbers of vehicles are increasing on the road, which leads to increase the road accident. So, it is very necessary for traffic management. Using ML method, we can predict the real-time traffic and easily solve this problem. Such types of the systems find the digital traffic flow using satellite map and routing-based information [19].

The gaming industry has grown-up extremely in the recent time. AI-driven applications are widely used to create interactive gaming experience for the users. Such agents can take a multiple roles such as teammates, player’s opponents, or other non-player characters [19]. Different fields of ML help the programmers to develop games that are well suited to the present market demands.

Current era is the digital and robotic era. There will be requirement of such machine which can be work without human intervention. This is leading the automation of machine. Some works are very difficult and lives threaten, like to learn to fly the helicopter or any vehicles. Such types of situation can be handling by implementing such types of simulators, which gives the similar types of environment for training purpose. Such simulators are implemented by using AI algorithms.

To make profit in financial market, it is necessary to analyze and predict the stock market trends. For this proper understanding and prediction, skills are required. This is possible by using ML algorithms. Reinforcement learning and SVM [19] are used to predict such types of market trends, which help us to maximize the stock profit with low risk.

Due to cheap and high speed internet connection, the internet is growing very rapidly with various internet devices, and these internet devices are connected with the help of IoT (Internet of Things). IoT includes some physical devices with internet connection to provide smart or intelligence applications in real world. Such types of physical devices are capable to analyze, process, and store the sensor data. These devices are some types of embedded machines which can be controlled from around the world using some processing elements and software.

“Internet of Things” is a combination of various software and hardware that support connectivity among the globe. IoT devices can sense the situation, processed data, and interact with others. It becomes a great and prominent technology which reduces the irregularities present in the real world. As it provided many solutions using advanced technology like radiofrequency identification (RFID) [20], QR codes, biometrics, sensor networks, and nanotechnologies will be the main pillar of the upcoming IoT, which helps in communication, embedding, real problem addressing like smart grid computing, e-health, manage e-transportation, etc. IoT maintains the required privacy during communication within the devices. In a simple way, we can say that IoT is everything that is around us and we can sense, connect, and communicate on the internet, e.g., smart rooms with fully equipped with sensors and embedded systems [20]. Table 1.2gives various works in RFID field time to time.

Table 1.2 Time line of investigation in RFID.

In IoT, all devices having their own unique IP address and sensors are the brains of this. These sensors can be microelectromechanical systems (MEMS) which respond results in the form of weight, temperature, time, sound, light, humidity, motion, pressure, etc., and take further action which is decided through programming [28]. The Internet is everything which is connected to all living thing and nonliving thing to exchange the information. Nonliving things like any machines or objects could be received and send information to each other, without human intervention.

Environmental problems are obtaining more consideration as the broad public develops more alert of the terrible significances of the environmental ruin causes. Current technological lead to spreads and increases in the carbon imprint. The development in this arena is concrete on green IoT (G-IoT). Latest few years there will be green support for managing various tasks. The G-IoT is projected to introduce substantial changes in daily life and would help to grasp the visualization of green ambient which joins our real world through these green systems (grid). G-IoT helps to decrease discharges and smog to make it environmentally convenient and surveillance and reduces the power consumption and functioning costs [28]. The aim of G-IoT is to become energy efficient in terms of the design and development of IoT. To become the energy-efficient procedures, IoT focused on decreasing the green house conclusion of current applications and amenities or to decrease the effect of greenhouse influence of IoT them self. G-IoT life cycle consists of G-design, G-production, G-utilization, and, finally, G-disposal/recycling to have no or very small effect on the atmosphere. As per global consultants Gartner, Inc. (GCG), ICT currently produces carbon discharges of approximately 0.86 MGT annually (about 2% of universal carbon discharges) and, if ICT including IoT, its decreasing effect of carbon dioxide (CO 2) emissions [29].