The Internet of Things and Blockchain Technologies Adaptive Trade Systems in the Virtual World

This chapter presents artificial and natural intelligence technologies. As part of the digital economy of the virtual world program, it is envisaged to increase the efficiency of electronic commerce and entrepreneurship; a similar task has been set by the leadership of the People's Republic of China. At present, thinking in the virtual world and China is radically transforming, along with methodological approaches to the development of trade policy and its tools in the digital economy. It is these circumstances that determine the relevance of the study, the results of which are presented in this chapter. Development of the fundamental foundations for improving the efficiency of electronic commerce and entrepreneurship in virtual world and China based on the virtual exchange of intellectual knowledge using blockchain technology and implementation multi-chain open source platform is the goal. An acceleration of scientific and technological progress in all areas of knowledge raises the task for ensuring the continuous growth of professional skills throughout the whole life.

Using AI Technology to Support Speaking Skill Development for the Teaching of Chinese as a Foreign Language

The teaching of Chinese as a foreign language can be supported by using AI technology. Traditionally, the non-native learners can only interact with the instructors and depend on them solely for speaking practices. However, with the advancement of AI technology, the learners can use AI technology for interactive speaking skill development. In this study, the learners were instructed to download an application at https://m.wandoujia.com/apps/6790950. The process on the preparation of this AI technology in supporting their speaking skill development can be accessed at https://sites.google.com/site/gohyi141/assignments/projectinteractivespeakingapp. By using this AI technology, the findings showed a tremendous affirmative responses pertaining to the use of this AI technology. Hence, AI technology should be encouraged in active utilization for the teaching of Chinese as a foreign language in particular and for all language speaking skill development in general.

Supply Chain Management for Agri Foods Using Blockchain Technology

The agricultural supply chain consists of many participants like producer (generally farmer), consumer (people who buy the product and consume them), wholesalers, and retailers. This system consists of many levels of mediator parties as well which have different policies of the commission. Due to the difference in these policies, the producers do not get their fair share of price. Due to the varying prices, consumers also suffer as they do not get the right quality of the product for the right price. There are no central records maintained regarding the transactions between the participants which could lead to many serious problems. To tackle the above-mentioned issues, we need a holistic approach that can provide solutions to most of the above issues. Here, blockchain-based solution can be used to achieve traceability (we can trace the whereabouts of the product, the origin of the product, etc.), transparency (so that a sense of trust is achieved), fairness (by removing the intermediaries), assurance of food safety and pricing (so that nobody has to bear the loss).

A Blockchain-Based Federated Learning

Conventional machine learning (ML) needs centralized training data to be present on a given machine or datacenter. The healthcare, finance, and other institutions where data sharing is prohibited require an approach for training ML models in secured architecture. Recently, techniques such as federated learning (FL), MIT Media Lab's Split Neural networks, blockchain, aim to address privacy and regulation of data. However, there are difference between the design principles of FL and the requirements of Institutions like healthcare, finance, etc., which needs blockchain-orchestrated FL having the following features: clients with their local data can define access policies to their data and define how updated weights are to be encrypted between the workers and the aggregator using blockchain technology and also prepares audit trail logs undertaken within network and it keeps actual list of participants hidden. This is expected to remove barriers in a range of sectors including healthcare, finance, security, logistics, governance, operations, and manufacturing.

An Analytical Study on Machine Learning Techniques

The last few months have produced a remarkable expansion in research and deep study in the field of machine learning. Machine learning is a technique in which the set of the methods are used by the computers to make prediction, improve prediction and behavior prediction based on dataset. The learning techniques can be classified as supervised and unsupervised learning. The focus is on supervised machine learning that covers all the predictions problem for which we had the dataset in which the outcome is already known. Some of the algorithm like naive bayes, linear regression, SVM, k-nearest neighbor, especially neural network have gain growth in this area. The classifiers of machine learning are completely unconstrained with the assumptions of statistical and for that they are adapted by complex data. The authors have demonstrated the application of machine learning techniques and its ethical issues.

Internet of Things (IoT) in Agriculture

Connected devices have access to every part of our lives with the increasing implementation of the internet of things (IoT), from home automation, health and fitness, automobile, logistics, to smart cities, and industrial IoT. Therefore, it is only natural that IoT, connected devices, and automation find their application in agriculture, and as such, greatly enhance almost every facet of it. In recent decades, farming has undergone a variety of technological changes, becoming more industrialized and powered by technology. Farmers have gained effective control and efficiency over the process of raising livestock and growing crops through the use of various smart farming devices. Within this chapter, the authors discuss and analyze the advantages of using IoT within agriculture. They present the IoT system architecture to allow smart farming. This chapter also covers the advantages of integrating the blockchain into the agricultural field. Case studies are included in the end for your reference.

Prospects of Machine Learning With Blockchain in Healthcare and Agriculture

Presently, machine learning (ML) techniques have gained considerable attention, with growing interest in various areas and applications. Healthcare, agriculture, and bioinformatics are the most identified areas to study with the help of ML. This chapter introduces about the basic principle of ML such as data, model, basic mathematical details of ML, and types of learning. The important aspect of ML is “how to teach a machine.” This chapter focuses on the types of learning: supervised, unsupervised, semi-supervised, and reinforcement learning. Some commonly used ML algorithms such as decision tree (DT), k-nearest neighbor (KNN), support vector machine (SVM), naïve Bayes, k-mean, q-learning, etc. are briefly discussed for understanding. Finally, the author offers the application of ML with blockchain that is reforming the traditional healthcare and agricultural sector to a more reliable means.

Google Stock Movement

Human beings tend to make predictions about future events irrespective of probability of occurrence. We are fascinated to solve puzzles and patterns. One such area which intrigues many, full of complexity and unpredicted behavior, is the stock market. For the last decade or so, we have been trying to find patterns and understand the behavior of the stock market with the help of robust computation systems and new approaches to extract and analyze the huge amount of data. In this chapter, the authors have tried to understand stock price movement using a long short-term memory (LSTM) network and predict future behavior of stock price.

Study of Risk Analysis in the Internet of Things

The internet of things (IoT) refers to a network comprised of physical objects capable of gathering and sharing electronic information. Internet of things will be connected with physical objects that are accessible through the internet. In general, IoT is a collection of all things in the world and that should be connected over internet. But in any technology, there exist some risk factor which will diminish the performance of an organization. In IoT, security of information is always a challenging task. Security is an essential pillar of the internet, ‘the' most significant challenge for the IoT. When the number of connected devices increases, the opportunity of risk factor in positive and negative side will work to implement the IoT. Risk analysis is the review of the risks associated with a particular event or action. In this chapter, challenges of security and analysis of risk have discussed to reduce the problems.

Integrating Blockchain With AI

The advancement in AI and blockchain can fundamentally reshape our way of working, learning, and almost our way of living. Though the research in both areas helps us in advancing our knowledge, it is even more advantageous by converging concepts of blockchain and AI (i.e., developing the thinking through blockchain). Blockchain is decentralized, distributed, and often a public system. Thinking, fundamentally defined as rationally concluding something, with a few known premises, is the fundamental concept behind AI and implementing the AI to become as close to human intelligence as possible; therefore, improvements in thinking are always welcomed. Both being incomplete, AI suffers from issues with trustworthiness, explainability, and privacy, while blockchain suffers in case of security, scalability, and efficiency. Bringing these two together can complement each other and make the system efficient. The chapter deals with various uses of integrating blockchain with AI. It also gives a brief on the uses of blockchain for improving both human and machine thinking.