Smart House Systems Research Articles

Development of Electrically Conductive Wood-Based Panels for Sensor Applications

This study investigates the development of electrically conductive panels for application as emergency detection sensors in smart house systems. These panels, composed of wood chips coated with polymeric methylene diphenyl isocyanate, were modified with carbon black and carbon fibers to enable detection of moisture, temperature, and pressure variations. Manufactured via hot pressing, the panels retained standard mechanical properties and exhibited stable performance under diverse environmental conditions. Carbon black-filled panels achieved electrical percolation at a lower filler concentration (5%) compared to carbon fiber-filled panels. The incorporation of carbon black reduced the electrical resistivity to 8.6 ohm·cm, while the addition of carbon fibers further decreased it to 7.7 ohm·cm. In terms of sensor capabilities, panels containing carbon fibers demonstrated superior sensitivity to moisture and pressure changes. However, carbon black was ineffective for temperature sensing. Among the carbon fiber-filled panels, those with 20 wt.% concentration exhibited the best performance for moisture and pressure detection, whereas panels with 40 wt.% carbon fiber content displayed the most reliable and consistent temperature-sensing properties.

A low-cost smart home automation for elderly who has Alzheimer’s or age-related memory loss

Technology, which is developing considerable in recent years, have influence on automation systems as well. With the advancement of the technology, people want to remote access systems and artificial intelligent systems that can consider for them. Nowadays, people started to tend smart house systems in order to facilitate their lives and to live more peaceful. In this study, a smart house automation system was designed on LabVIEW platform for people who has age-related memory loss or Alzheimer’s or who cannot fulfill their needs. The house performs some functions namely, medication reminder, pulse-control sensor, temperature control and fire alarm, door/window warning system, burglar alarm, and lighting systems. This study is based on, communication via e-mail. If there is any abnormality in the house, the system allows users to have an e-mail about the current situation. Since, the study targets elderly or people who needs medical care, this low-cost design can be very preferable in the future.

Optimal Artificial Neural Network Type Selection Method for Usage in Smart House Systems.

In the process of the “smart” house systems work, there is a need to process fuzzy input data. The models based on the artificial neural networks are used to process fuzzy input data from the sensors. However, each artificial neural network has a certain advantage and, with a different accuracy, allows one to process different types of data and generate control signals. To solve this problem, a method of choosing the optimal type of artificial neural network has been proposed. It is based on solving an optimization problem, where the optimization criterion is an error of a certain type of artificial neural network determined to control the corresponding subsystem of a “smart” house. In the process of learning different types of artificial neural networks, the same historical input data are used. The research presents the dependencies between the types of neural networks, the number of inner layers of the artificial neural network, the number of neurons on each inner layer, the error of the settings parameters calculation of the relative expected results.

双方向インバータを用いたスマートハウスの経済運用に関する研究

Introduction of the renewable energy and energy-saving technologies that contribute to reducing environmental impact, this research have focused on smart house systems. There is few research on the economics of smart houses involving storage batteries, and the optimal operation method of a battery introduced into an individual houses based on economical efficiency is not clear. Therefore, in this research, the authors try to optimize operation method of storage battery on an individual house of one day by bi-directional inverter for smart house system. In the proposed system, purchase from the commercial power system is minimized by optimal operation of the bi-directional inverter on the predicted data of the energy balance and solar radiation amount of the next day. In addition, surplus electric power obtained by solar power generation is sold to electric power company. The proposed system consists of solar cells, storage battery, bi-directional inverters and simulated load. A bi-directional inverter optimization algorithm is installed into the controller of the proposed system. The operation of the controller is optimized by the genetic algorithm (GA), and the objective function gives the minimization of the amount of purchase electric power per one day.

ETHICS OF SMART HOUSE WELFARE TECHNOLOGY FOR OLDER ADULTS: A SYSTEMATIC LITERATURE REVIEW.

The University College of Southeast Norway has an on-going project to develop a smart house welfare system to allow older adults and people with disabilities to remain in their homes for as long as they wish in safe, dignified, living conditions. This article reviews reported ethical challenges to implementing smart houses for older adults. A systematic literature review identified twenty-four articles in English, French, Spanish, and Norwegian, which were analyzed and synthesized using Hofmann's question list to investigate the reported ethical challenges. Smart houses offer a promising way to improve access to home care for older adults and people with disabilities. However, important ethical challenges arise when implementing smart houses, including cost-effectiveness, privacy, autonomy, informed consent, dignity, safety, and trust. The identified ethical challenges are important to consider when developing smart house systems. Due to the limitations of smart house technology, designers and users should be mindful that smart houses can achieve a safer and more dignified life-style but cannot solve all the challenges related to ageing, disabilities, and disease. At some point, smart houses can no longer help persons as they develop needs that smart houses cannot meet.

A Novel Type of Wireless V2H System with a Bidirectional Single-Ended Inverter Drive Resonant IPT

Electric vehicles (EV) offer promise as an effective solution to environmental problems. One of the keys to their successful diffusion is the provision of adequate battery charging infrastructure. In order to create a charging infrastructure by installing equipment in such as locations as carports in private homes, the wireless battery charging system is very suitable. EVs can be used in smart house systems to supplement the energy storage. This vehicle to home (V2H) system essentially requires a bidirectional power transfer feature between the EV and home. This paper presents a new bidirectional inductive power transfer (IPT) system for wireless V2H with simplest components and low cost aiming at wide diffusion for home use. Proposed is a novel type of bidirectional wireless EV charging system with an efficient and compact type single-ended quasi-resonant high-frequency inverter for V2H.

Human Tracking Methods Comparison for Smart House Method Comparison in Human Tracking for Smart House Purpose

Smarthouse systems require some information of human locations in the system environment, different smart house system offers different human tracking method. The idea of this paper is to determine which method is better in which condition. This paper discusses amongst RFID, voice recognizer and temperaturesensor. As a result, each method have its own advantages and disadvantages.
 Index Terms - smart house, human tracking, voice recognition RFID, Sensor.