Intelligent Environmental System Research Articles

Contextual Awareness Service of Internet of Things User Interaction Mode in Intelligent Environment

In order to reduce the difficulty of the Internet of Things intelligent environment system to provide users with layout services and optimize the system structure, this paper proposes to design a context-aware service system based on the user interaction mode of the Internet of Things. This article first collected a large amount of data through the literature survey method, which laid a sufficient theoretical foundation for the subsequent research; then, using smart sensors, smart interaction technology, and context awareness methods is employed to design and build a context-aware service system based on the user interaction modality of the Internet of Things; in order to test the performance and effect of the situational awareness system, take the elderly home care behavior as the research object, collect the 28-day home behavior of the elderly as sample data, and divide it into 7-day data, 14-day data, 21-day data, and 28-day data, by adopting rule pruning demand reasoning algorithm and evidence theory algorithm to reason about the service demand of the elderly. Finally, the experimental results show that the rule-pruning-based service demand reasoning algorithm combined with the evidence theory algorithm optimizes the system, which can better perceive the situation of the elderly living alone and can well reason about the elderly’s service demand, which is of great significance for solving the life and safety problems of the elderly.

A statistical analysis of air-pollution before COVID-19: experimental study of three years for intelligent environment conducted at North Indian Zone to extract knowledge

In populated and developing countries, governments consider the regulation and protection of the environment as a major task and should take into consideration the concept of smart environment monitoring. The main motive of these systems is to enhance the environment with various technology including sensors, processors, datasets and other devices connected across the globe through a network. This system can basically help in monitoring air quality which is necessary in the field of meteorological studies and movement factors. Also, these factors contribute a lot in air pollution. So, forecasting air quality index using an intelligent environment system, which includes a machine learning model in order to predict air quality index for National Capital Region (NCR) was proposed. The values of major pollutants like SO2, PM2.5, CO, PM10, NO2, and O3 were used. In recent years, machine learning in most emerging technology is used for prediction with 99.99% of accuracy by using historical data.

Intelligent Environment System Based on CIM

The construction of smart city has added a lot of charm to our country, and has been paid attention to by everyone, but there are still environmental pollution problems. The emergence of urban information model technology (CIM) makes the construction of three-dimensional composition combined with environmental perception to solve this problem. In this paper, the intelligent environment system based on CIM is studied, which is based on the requirements of intelligent environment system. Starting from the basic content of CIM, the smart city construction and CIM technology are combined, and the architecture of CIM intelligent environment system is established through data collection, wireless communication, micro processing and other aspects. Aiming at the non-uniformity of the system itself and the inaccuracy of the temperature measurement distance, the error caused by the temperature perception of the furnace wall is corrected. The Kalman filter algorithm is used to eliminate the noise and redundancy, and the accuracy of the collected data is improved. The experimental results show that the system can monitor the environmental problems intelligently in real time, and the accuracy rate is as high as 89.38%. It can effectively monitor environmental changes and prevent large-scale environmental pollution.

Tree of life – intelligent environment system station design

The three elements essential for life are sunshine, air, and water. This is an undeniable fact, but with advancements in technology, amenities such as electricity, smart phones, and the internet have become the urban versions of these essential elements for life. Most people living in cities desire constant connectivity. This connectivity requires significant electricity and access to a high-speed internet connection. The purpose of this research is to design a wind turbine system modelled after the shape of a tree with the blades built inside the tree. The power generated by the tree will be stored in a power bank located inside a station adjacent to the tree and will be available to the public. Additionally, there will be WLAN antennas built inside the tree branches to provide wireless internet signals. Finally, the electricity produced will be green energy, which will help us achieve the goal of eco-friendly but intelligent life.

Smart home simulation model for synthetic sensor datasets generation

World population is ageing due to longer life expectancy worldwide. There is a trend in elderly people to live alone in their habitual residences in spite of health and safety risks. Smart Homes, intelligent environment systems deployed at elderly homes can act as early warning systems trying to forecast the worsening or exacerbation of the resident chronic conditions. Access to sensor datasets is essential for the development of an efficient real smart home. Procurement of such datasets is subject to several restrictions and difficulties. This paper describes the generation of synthetic datasets by means of a simulation model as a suitable alternative previous to the deployment of a real monitoring system. The collection of synthetic datasets will be used during the next project step to train and evaluate activity recognition methods and algorithms.

省エネルギーを考慮した空間知能化システムとその通信方式

A Smart House is watched in order to improve environmental issue and accelerate energy conservation by reducing energy consumption. Smart House technology provides its home owners comfort, security, energy efficiency and convenience at all times. On the other hand, intelligent environment system is advanced with the rapid progress of M2M/IoT and sensing technologies. It is necessary to utilize low energy consumption technology for the implementation of Smart House. Intelligent space system has an ability of monitoring the behavior of a person in house and checking normal behavior or abnormal behavior. This paper proposes an effective communication method in an intelligent space by using energy conservation technology and low energy communication method. We applied the proposed method to a prototype of a watching system for a person living in a remote house, and evaluated the effectiveness of the communication method.

The application of statistical reliability theory in the context of Intelligent Environments: a tutorial review

Intelligent Environments often require the integration of multi-modal sensing and actuating technologies with high performance real-time computation, including artificial intelligence systems for analysis, learning patterns and reasoning. Such systems may be complex, and involve multiple components. However, in order to make them affordable, Intelligent Environments sometimes require many of their individual components to be low-cost. Nevertheless, in many applications—including safety-critical systems, and systems monitoring the health and well-being of vulnerable individuals, it is essential that these Intelligent Environment systems are reliable, which the issue of affordability must not compromise. If such environments are to find real application and deployment in these types of domain, it is necessary to be able to obtain accurate predictions of how probable any potential failure of the system is in any given timeframe, and of statistical parameters regarding the expected time to the first, or between successive, failures. Such quantities must be kept within what are deemed to be acceptable tolerances if the Intelligent Environment is to be suitable for applications in these critical areas, without requiring excessively high levels of human monitoring and/or intervention. In this paper, an introductory overview of statistical reliability theory is presented. The applicability of this to the context of Intelligent Environments—particularly those involving safety critical or other sensitive issues—is discussed, along with how such reliability modelling can be used to influence the design, implementation and application of an Intelligent Environment.

Introduction to the inaugural issue of the Journal of Reliable Intelligent Environments

As envisioned by Weiser, computing is in the process of being everywhere and becoming invisible. As Milner noticed, the question now is whether we shall understand this ubiquitous computer we are building. This is especially true as designers are more and more using complex techniques for every component of the system and building systems which are made of increasingly heterogenous parts. With this extended editorial, we embark on an exploration journey into the exciting new area of “reliable intelligent environments” (RIEs). Taking the perspective of an RIE engineer, we present a selection of approaches that have been put forward to design, verify, and operate IEs in a manner so that users can rely on Intelligent Environment systems. We outline crucial challenges: the situatedness which exposes IE to challenges similar to those known from robotics and control systems, the embedding of human users and the safety, privacy, and usability requirements thus entailed, and the amounts of data produced by sensors and actuators, which require advanced reasoning and learning mechanisms to handle them in a reliable way in real-time. We also sketch the opportunities reliable IEs provide to developing new markets and products.

Distributed Web-based Management Framework for Ambient Reconfigurable Services in the Intelligent Environment

Existing and emerging technologies in the areas of mobile computing, wireless communications/ networking, sensor and control devices, context awareness, user interfaces, etc., provide the ground for the support of human activities in a certain space. More specifically, these recent advances now allow the gradual "disappearance" of computers and/or other end-user devices into the environment creating a system that can facilitate everyday living. Such an intelligent environment system offers personalised, context-aware services that can support and improve everyday life. In spite of the large number and variety of devices, networking technologies and ambient intelligence sub-systems there is a lack of a framework that brings the different relevant actors together and exploits the full potential of emerging technologies to meet the requirements of an intelligent environment system, not only in the context of the home but also in the corporate and public sectors. Intelligent environments necessitate new, advanced management mechanisms. This paper presents an approach for a Distributed Web-based management framework for ambient reconfigurable services in the intelligent environment (DAFNE).