Development and Implementation of the Smart Village Concept as a Challenge for the Modern Power Industry on the Example of Poland

Nowadays, while cities are often subject to research in terms of their development, especially smart development, studies on rural areas are rare. However, the development of the latter is very important. It is important that rural areas develop economically and socially. Smart villages are a challenge for the modern energy sector. The authors of the article try to answer the question: What are the challenges for the modern energy sector in the context of rural development? The aim of this article is to identify challenges for the modern power industry in the concept of smart countryside development. The article begins with the presentation of the essence of smart villages and the essence of energy policy. The research facilitated the identification of basic challenges that prevent or slow down the development of the smart villages in terms of modern energy solutions, as perceived by experts and residents, and farmers and entrepreneurs operating in rural areas. The article identifies a number of energy challenges in the context of a smart village. They include, among others, a lack of awareness regarding the impact of energy on the environment, a low level of public knowledge about new energy solutions, and a lack of social trust in modern energy solutions in rural areas. The research was conducted in rural areas in the north-western part of Poland. At the end, the article presents a model of rural development in the context of the modern energy sector. The research also allowed the creation of a smart village development model that focuses on smart economy, intelligent environment, intelligent people, and intelligent governance. Since these are universal solutions, they can be used as a proposition for other countries.

Design of Intelligent Environment Observation and Decision Support for Regional World Economy

In order to avoid the risk of marginalization of low-level areas in the process of economic globalization, regional economies have also developed from this, which is important for the regional world economy in a smart environment. Observation and decision support have also attracted much attention from academia. Based on the important situation of regional world economic development, scholars have conducted a lot of research studies; this paper studies the development trend of the regionalized world economy in the intelligent environment under the network of interconnected objects and uses decision support technology and sensor networks to observe and design decision support for the regionalized world economy. Association rule mining technology is used to conduct data mining and data collection on the relevant data in the regionalized world economy, cluster analysis is used to sort and calculate the mined experimental data, and the experimental data model is extracted through the decision tree algorithm. This study collects various data on the number of trade agreements in 2015–2019, the expansion of free trade zones, the import and export trade rates of the EU, North America, and the Asia-Pacific region, and the currency circulation in each region of the world and also organize, observe, and analyze the regional world economy. The final results show that, from 2015 to 2019, free trade areas in various regions of the world are expanding every year. There are 12 free trade areas in Western Europe, the Middle East, the Mediterranean, Central and Eastern Europe, and Russia. At the same time, North America, Asia-Pacific, and the EU pay more attention to intraregional trade, especially the annual trade rate of the EU of more than 50%. The regional world economy still has a trend of development in modern society and even in the next few decades, and the regional world economy has a certain role in promoting the economic development of various countries and regions. The regional world economy still has a development trend in modern society and even in the next few decades. It has a certain promoting effect on the economic development of various countries and regions. It is an inevitable trend of world economic development and the only way to economic globalization.

Context-Induced Activity Monitoring for On-Demand Things-of-Interest Recommendation in an Ambient Intelligent Environment

Recommendation systems are crucial in the provision of services to the elderly with Alzheimer’s disease in IoT-based smart home environments. In this work, a Reminder Care System (RCS) is presented to help Alzheimer patients live in and operate their homes safely and independently. A contextual bandit approach is utilized in the formulation of the proposed recommendation system to tackle dynamicity in human activities and to construct accurate recommendations that meet user needs without their feedback. The system was evaluated based on three public datasets using a cumulative reward as a metric. Our experimental results demonstrate the feasibility and effectiveness of the proposed Reminder Care System for real-world IoT-based smart home applications.

Intelligent Environment Platform for Industrial Clusters Based on Cloud Computing Technology

With the development of science and technology and the improvement of industrialization, the development of more and more industries has interacted to form many industrial clusters. For the healthy development and safety of various industries, environmental quality monitoring and management in industrial clusters is of utmost importance. Currently, domestic and foreign enterprises and related departments are vigorously developing smart environment platforms. The purpose of this paper is to design an intelligent environment platform for industrial clusters based on cloud computing technology. This article first uses the methods of literature research and network investigation to collect relevant literature and research results and organizes statistics on the collected information. Then, through case analysis to study the needs and overview of the construction of smart environment platforms in industrial clusters, it uses the wireless smart sensing technology of the Internet of Things and the information interaction technology of the Internet to provide data to cloud computing through mobile terminals, and cloud computing provides various types on demand data service. Then, according to the demand analysis of the intelligent environment platform, the functional modules and operation procedures of the intelligent environment platform are designed. The main monitoring content is water quality testing, air quality testing, garbage disposal and soil quality testing, etc. Finally, this article processes, analyzes, and predicts the detected sampled data through cloud computing. It can also locate and track abnormal data. Through the curve fitting of the data, the environmental conditions in the area can be predicted. Experiments show that the prediction accuracy rate is as high as 93.8%, which plays an important role in monitoring and preventing environmental pollution.

The Construction of the Fusion and Symbiosis Path of Infant Sports Development Based on Intelligent Environment

In view of the differences and uniqueness of intelligence between people, the application of new educational thoughts is the need of the time; in the educational atmosphere created by the intelligent environment, it is urgent to seek a path of integration and symbiosis. This article takes the development of children's sports driven by the intelligent education project as the main research object, selects our city's children's football as the representative of sports events to carry out case studies, and uses the spectrum education program to explore the intelligent development of intelligent children with logical and mathematical advantages in the field of sports. This paper designs a data fusion method for homogeneous smart sensors. The correlation degree of the nodes in the continuous sampling period is obtained by defining the spatial correlation coefficient, and the confidence value and coherent degree of integration are obtained by applying the angle of attraction between nodes in the definition of fusion strategy in the evaluation of neighborhood, and lastly, the node coefficient of weight is reallocated to validate the fused expression. The feasibility of the simulation is used to confirm the trustworthiness of the solution. Based on the development status of children’s physical education, this article uses intelligent mobile networks to find out the problems in the physical education classes of kindergarten teachers and the problems that are not compatible with the development of children’s physical education. The kindergarten normal students receive targeted physical education and acquire solid professional skills. The study indicates that the percentage of basic motor and basic motility classes in the city's kindergartens is 100%, suggesting that all preschools in the city operate fundamental motor practice classes for a group of children. They have fully realized that basic movement exercises have an impact on children’s body shape.

Course Ideological and Political Teaching Platform Based on the Fusion of Multiple Data and Information in an Intelligent Environment

In the current teaching of politics, teachers still focus on the cultivation of the basic intelligence of students’ language intelligence, and it is easy to ignore the cultivation of other intelligences that affect the overall development of students. This research mainly discusses the design of curriculum ideological and political teaching platform based on the fusion of multiple data and information in an intelligent environment. This research adopts the MVC architecture, and the web application developed based on the MVC (Model View Controller) architecture pattern is easier to complete the realization of multiple controllers. The front desk ideological and political teaching teacher module includes the login system. In addition, the teacher can view the test status of a specific student and can also pay attention to the total intelligence of all students who have been tested. The process of the student test is to enter the correct account and password to log in to the system and then perform the test. After the test, the test result can be viewed, and the personal information can be maintained at the same time. In addition, the personal login password can be modified. The existence of the database is to ensure that the data is correct and effective. This system uses MySql to design the database, and the name of the database is braintest_db. The data table in relational database is the main object of storing and managing data, and it is also an important task of database design. This system has designed three kinds of user logins, namely, administrator, student, and teacher, and login can be realized according to the account number and password. Among them, teacher’s participation is by inquiring about students’ test situation, paying attention to students’ multiple intelligences, and teaching students in accordance with their aptitude. In addition, the main object of this test is students, and the analysis of multiple intelligences is realized through student tests. Students are vitally physical objects that can be tested and searched for results. In the study, 20% of the students both learn the basic content of the platform and use the forum. This research will help improve students’ literacy in an all-round way.

An intelligent environment for manufacturing creative-aesthetic products

Providing a product with characteristics of beauty and creative innovation is one of the aims of any contemporary industry to meet the needs of customers and satisfy their aesthetic and functional requirements. To study the production process and the realisation of creative products with aesthetically pleasing attributes, we created a smart production environment that allows the construction of simple textured polygons (triangles, squares, rhombuses and pentagons) through a software application. Birkhoff aesthetical measure, Euclidean Distance and Entropy Measure have been developed and applied to a sample of smart products, manufactured in the implemented environment, to analyse their aesthetical, creative and the order-complexity-chaos features respectively. The results provided us with measurable quantities of the sought qualities for the sample and for each distinct product, combining the metrics to visualise the creative space in two and threedimensional spaces. Further mathematical methods, such as Point Process and Density Probability Map applied on the same sample, allowed us to move from a statistical space to probabilistic landscapes, with enhanced forecasting capability on creative features for all future products. Industrial applications are expected in the production and evaluation of products from a creative point of view.

Convolutional Neural Network Based Intelligent Advertisement Search Framework for Online English Newspapers

Background: Instant access to desired information is crucial for building an intelligent environment that creates value for people and steering towards society 5.0. Online newspapers are one such example that provides instant access to information anywhere and anytime on our mobiles, tablets, laptops, desktops, etc. However, when it comes to searching for a specific advertisement in newspapers, online newspapers do not provide easy advertisement search options. In addition, there are no specialized search portals for keyword-based advertisement searches across multiple online newspapers. As a result, to find a specific advertisement in multiple newspapers, a sequential manual search is required across a range of online newspapers. Objective: This research paper proposes a keyword-based advertisement search framework to provide an instant access to the relevant advertisements from online English newspapers in a category of reader’s choice. Method: First, an image extraction algorithm is proposed to identify and extract the images from online newspapers without using any rules on advertisement placement and size. It is followed by a proposed deep learning Convolutional Neural Network (CNN) model named ‘Adv_Recognizer’ to separate the advertisement images from non-advertisement images. Another CNN Model, ‘Adv_Classifier’, is proposed, classifying the advertisement images into four pre-defined categories. Finally, the Optical Character Recognition (OCR) technique performs keyword-based advertisement searches in various types across multiple newspapers. Results: The proposed image extraction algorithm can easily extract all types of well-bounded images from different online newspapers. This algorithm is used to create an ‘English newspaper image dataset’ of 11,000 images, including advertisements and non-advertisements. The proposed ‘Adv_Recognizer’ model separates advertising and non-advertisement pictures with an accuracy of around 97.8%. In addition, the proposed ‘Adv_Classifier’ model classifies the advertisements in four pre-defined categories exhibiting an accuracy of approximately 73.5%. Conclusion: The proposed framework will help newspaper readers perform exhaustive advertisement searches across various online English newspapers in a category of their interest. It will also help in carrying out advertisement analysis and studies.