Abstract
1. Introduction
As information technologies (ITs) have rapidly been updated and evolved, things and environments around our societies have also been rapidly changed. In particular, emerging smart phones and sensor technologies have made individual's life style smarter, more convenient, and more efficient. By recognizing environment changes and human's behaviors, wireless sensor networks are able to reduce upcoming hazards and improve efficiencies in daily life. Such changes are also coming to our living environment represented by smart home. Recently, many houses, called “smart home,” are equipped with lots of sensors and networks to provide some automatic or prediction services. However, even though it is certain that smart home makes our lives easier, people do not benefit from smart home that much. Particularly, the elderly people has difficulties in using such smart functions because the level of adaptation of the old people to the new environment and era is insufficient.
UN classifies three societies depending on the proportion of the elderly in the population (more than 65 years old) takes in a society: aging, aged, and super aged societies. According to the classification defined by UN, aging society refers to a society of less than 7% to 14% population ratio for the elderly people who aged 65 and more in total population. Society of 14% to 20% elderly people ratio would be referred as an aged society, and society of more than 20% of elderly people ratio would be a super aged society. As shown in Figure 1 [1], many countries rapidly move forward to the aged society. Population of aged people is increasing in nearly all regions. Even more, some of few countries are heading to super aged society passing through the aged society. Figure 2 illustrates the trends of the elderly population growth in Korea. As shown in Figure 2, the ratio of 11% of the elderly of the total population in 2010, 24.3% in 2030, and 40.1% in 2060 would be expected to be grown in total population ratio. Particularly the ratio of more than 85-year-old people will be from 0.7% in 2010 to 10.2% in 2060, and it shows they are increasing 10 times [2]. In accordance with the Statistics Korea, the elderly ratio was over 10% of total population ratio in 2010, and the ratio would be 20% in 2026. So then, after 12 years, the elderly will be a person out of 5 people, and that is called the super aged society [3]. Thus, the aged society is on-going so fast in the Republic of Korea. Therefore, many countries have studied issues that can possibly occur for the upcoming society and have been preparing to cope the issues.
Proportion of population aged 60 or over by region in 2014, 2030, and 2050.
Trends of the elderly population growth in Korea.
One of the issues that the aged society faces might be the elderly's housing. There are a few papers addressing the importance of housing for the elderly's life [4] and the importance is increasing as the number of old people increases. Furthermore, even though the old people is restricted in their activities due to physical degradation, health issues, and so forth and thus, they need more help than younger people does, the number of elderly people living alone is increasing as shown in Figure 3. Therefore, designing the elderly's housing is getting important. With increasing the interest of the elderly housing and tremendous growths of information technologies (ITs), smart home technologies are also paid attention for proving the better life for the elderly [5]. However, even though the elderly and health professionals consider smart home technologies to be beneficial [5] and many services and systems for the elderly's housing have been designed and developed, there are many issues to be resolved such as privacy, cost, and feasibilities. Furthermore, some of the smart homes provide unnecessary services for elderly people because only technical services were formed without carefully considering specific user classification (such as the elderly) that is optimized to particular needs and services for the elderly [6]. To design IT services/systems for smart home, it is important to take into account the fact that learning ability in new environment is not commensurate for real because the elderly and the semielderly are physically and mentally less active than normal adults are, and learning ability for the new skills for them is also low [7].
Increasing trends of the number of the elderly and the number of the elderly living alone in Korea.
In this paper, we propose research directions for designing cognitive sensor network-based smart home for the elderly through revisiting the definition of smart home and briefly surveying context-aware or cognitive sensor network-based smart home technologies for the elderly. Unlike sensor network technology-oriented research directions conducted in many preexisting studies, this paper propose sensor network research directions in terms of cognitive radio technology, usability, and cooperating with architectural technologies. In other words, this paper provides some idea to effective architecture design process for the elderly housing by converging cognitive sensor network technologies with architecture engineering.
The paper is organized as follows. Section 2 is divided into three parts. In the first part, we try to clearly define a smart home by revisiting previous studies. The second part describes the current cognitive sensor network-based smart home technologies for the elderly and looked at its problems. We have also investigated the emerging technologies in a smart home. Through these feasibility studies, in Section 3, four directions for designing the elderly's housing in terms of cognitive sensor network technology itself and the convergences of network technologies and the architect technologies are discussed. Finally, the paper is concluded through the conclusion in Section 4.
2. Case Studies
2.1. Smart Home
The definition of a smart home can be the living environment providing the convenience and efficiency with comforts and security to the resident using the IT technology as shown in Figure 4. According to Wilson et al. [7], functionally, smart home is a residential environment that implements automated and active control and senses and monitors various situations. Instrumentally, it is an optimal management building itself with real-time information and a price-responsive control of the housing environment. In sociotechnical aspects, smart home is a vision of the future living environment that is automatically and technically connected to everything [7]. In addition, the Korea Association of Smart Home (KASH) [8] defines it as the human-centered smart life environment that enables convenience, welfare promotion, and safe life for the people by converging IT technology to a residential environment. In other words, KASH defines a smart home as a spatial environment including all living-related services and systems rather than home itself. Smart home that is an evolved version of currently existing home has appeared by embedding information and communications technologies into a house. This allows the improvement of the quality of life through new and better features, the reduction of energy consumption, and enhanced system management at home [9]. In addition, this helps the resident to satisfy their needs besides basic needs that they can have at home. Except for the existing residential characteristics provided to residents, the organized main function of the smart home provided to users is as follows.
Circulation of the smart home.
At first, smart home can give us comfort. Not only the existing house could be comfortable, but also the smart home brings us comfortable convenience because the housing environment could take care of many little things that users should do. Secondly, it is safe. The existing home is bad at protecting from against invasions from outside, accidents for solitary residents in their house, or other emergencies. However, the smart home system could be safe because of the monitoring system from outside invasions, and also it could take follow-up measures of the accident because of immediate notification to other people by sensing and monitoring an accident of residents inside. At last, it is efficient and saves energy. The users, because of human-being, might not be perfect. This means they could waste energies by mistakes or accidents such as turning on lights or water and so forth even if they were not using. There would affect saving energies if the living environment could detect and prevent those wastes. Furthermore, it could be efficient for preventing redundant energy uses such as using heater and air conditioner at the same time. For these reasons, a smart home provides users with more advanced living environments and benefits as compared with the traditional house.
2.2. Sensor Network-Based Systems for Smart Elderly Housing
In this section, we investigate studies focusing on developing sensor network-based IT systems/services for the elderly housing which are published after the year 2010 while Morris et al. [5] survey effectiveness and feasibility of general smart home IT technologies. As many information and communication technologies have been developed and evolved like Internet of Things (IoT), long-term evolution (LTE), smart phones, and so on, a few technologies in a smart home for the elderly have been introduced. Even though sensor network-based IT systems/services for normal people have been proposed a lot, the number of them for elderly housing is relatively small. While the researches on areas such as safety, privacy, reliability, efficiency, and technology correlated with smart home issues are in progress, smart home technology for the elderly is mostly being developed only for health care or safety. Suryadevara et al. [10] have proposed a system of protecting the elderly in the smart home using a wireless sensor network. The authors monitored in real time for their life in weekends and on weekdays by equipping the ZigBee wireless sensor on their appliances and things. With the data, a system was designed for separating normal behavior and abnormal behavior. Charlon et al. [11] propose a more effective location-based monitoring system for the elderly people with dementia. Until now, this real-time patient monitoring system is using infrared-ray sensors. However, monitoring elderly patients and preparing for the safety accidents would be now from attaching the wireless sensors in the form of patches to the elderly's back. Lee et al. [12] proposed a smart environment in bathroom based on the sensor networks. The study addresses that 48.8% of the safety accidents are fall accidents in bathroom based on the statistical analysis of safety accidents for the elderly in 2010. In order to help the elderly's activities in the bathroom, the authors define several living patterns and based on the patterns, the system provides convenient services for the elderly to use bathroom safely. Portet et al. [13] report user evaluation how well the elderly accept voice-command-based home automation systems, which is implemented as a part of SWEET-HOME project, and what sort of benefits can be obtained. SWEET-HOME project is supported by a French and aims to realize man-machine interaction based on audio processing. In the study, the elderly assesses that speech technologies have potential to ease their life. The noteworthy point is that the technology is more effective in securing their lives than in comfort improvement. Kim et al. [14] propose a monitoring system of U-health smart home for the elderly. Hardware and software of the smart home ontology model (SHOM) and common information model (CIM) were developed and implemented by equipping various sensors. However, this study develops the system for just health monitoring system and energy management system with SHOM. Other systems of health-related as healthcare or behavior pattern prediction are not implemented. Shen et al. [15] propose TV-based videophone system for the elderly in smart home. Because TV does not only come into wide use so that the elderly need to pay more money for the videophone system but also is low cost device with high resolution and large screen which is fit for the elderly, the authors select TV for the videophone system for the elderly. In addition, using Support Vector Machine (SVM) algorithm, the system is able to evaluate “rough” physical and psychological health information of the elderly. This evaluation is performed based on the frequency and the length of using the system of the elderly at home. Lee et al. [16] propose ubiquitous-care system for the elderly in smart home environment. The system provides services to track old people's location inside house, to monitor indoor environment parameters such as temperature and humidity, and to send short message to guidance just in abnormal cases. The proposed system is fit to houses equipped with lots of sensors and well organized networks, which seems infeasible. Yu et al. [17] propose a computer vision-based fall detection system to monitor an elderly person who lives alone at home. The system detects the old people's fall based on posture recognition using a single camera. From the experimental results, the system achieves 97.08% fall detection rate and 0.8% false detection rate on a 15 person dataset. Ransing and Rajput [18] propose a simple home safety system for the elderly by utilizing the wireless sensor network with ZigBee protocol. If the temperature increases abnormally in a particular space, the system will inform the current temperature and send warning messages to the users at the same time. The studies are oriented more to implement wireless sensor networks rather than to resolve issues on elderly housing. Kim et al. [19] propose location tracking system inside smart home for elderly safety. Using RFID technology, this system could monitor locations of the elderly in real time for prevention of abnormal situation if unexpected patterns occurred. In addition, they propose module structures of this healthcare system for elderly people. Those are the tag sensing module, location sensing and tracking module, monitoring module, alarm module, health status information module, and external communication module. These modules are for operating process of this proposed system such as sensing, recording, analysis, and feedback. Table 1 lists not only summaries of contents, but also the targeted functions of all studies mentioned above.
Summary of prior-arts related to smart home systems for the elderly.
As aforementioned above, smart home technologies for the elderly focus on relatively narrow area comparing to that for common people. For example, as mentioned before, most of smart services for the elderly are health care and safety systems as shown in the “targeted function” column in Table 1 while smart home for general people has various areas including energy reduction/management, invasion detections, home security, and automated environmental change system. Because society is increasingly aging, and elderly housing types for single old person or the elderly's community are expected to be emerging, studying IT services utilizing cognitive sensor networks for elderly housing is necessary to be accomplished in various areas. One of these areas might be energy or electric power-related area specialized for the elderly. For example, since the old people have the lack of memory abilities, they might forget to close windows at their house before turning on air-conditioner, which wastes electric power.
2.3. Energy Saving in Smart Home
As mentioned at the end of the previous section, even though many areas are involved in designing smart home for the elderly, IT services for elderly housing are somewhat limited to health and safety. Therefore, we may extend the study area to the other areas such as efficient energy use just like normal people's houses. As a part of this, energy-related IT systems for elderly housing are survey in this section. However, since as far as we researched, few studies about energy consumption-related issues for elderly housing are reported, we instead survey energy-related IT systems for smart homes in terms of IT technology itself. Han and Lim [20] propose a context prediction-based Smart Home Energy Management System (SHEMS) that is based on the data collected from wireless sensors, whose data transmissions are performed based on Kruskal's algorithm. However, the proposed system is somewhat close to smart service system rather than energy management system. Baig et al. [21] propose Energy Management monitoring System (EMS) and a scheduling method for the system. The method schedules appliances' operation times for each appliance to be operated in particular times when the price of using electric power is low. As a result, while the electric power is used about same amount, the user are able to use it with less price through appropriate scheduling for the low energy costs. Mahmood et al. [22] propose Home Appliances Coordination Scheme for Energy Management (HACS4EM) by communication among smart appliances, Energy Management Unit (EMU), and wireless sensor home area network (WSHAN) using ZigBee wireless sensor networks. With communication of these units, the EMU sets the schedule time of the effectively usable periods for the appliances and then suggests the convenient start time to user because the purpose of this system is to reduce the electricity cost from high to low by controlling the operation time. Usman et al. [23] design a routing protocol in order to transmit information by clustering the wireless sensors. In the clusterization, each of nodes is grouped, each of cluster headers is routed to the other cluster header or base stations, and as a consequence, the data can be transmitted further and faster to the destination. This wireless sensor network could be better efficient in terms of energy consumptions of the nodes. Han and Lim [24] propose multisensing and light control application based on smart energy control system for reducing energy costs by using smart energy networks including both ZigBee and IEEE 802.15.4 because one of energy consumptions in home environment is lighting. The reason why Han used both ZigBee and IEEE 802.15.4 is that various manufactured ZigBee devices were used for the interoperability in a system. Through the sensing environment and its data transferred by the wireless networks, the lighting system for reducing electric power would be effectively automatically turned light off or down as befits the environment. Arvind and Ramaswamy [25] develop smart monitoring and controlling system that manages energy usage of home units to be sensed and controlled by using a ZigBee communication module for wireless sensor network. Particularly, it designed to use the minimum energy though temperature monitoring devices with in-built temperature sensor in rooms and communications among the sensors in a building. In addition, software recovery procedures such as exception-handling, autorestart, and alert text mechanism for sensors failure were developed as well. Lampoltshammer et al. [26] propose a method to reduce the energy consumption of the wireless sensor nodes in the health monitoring system for the elderly. The more the data transactions in wireless sensor nodes are increased, the more the energy consumption is increased. In order to reduce the amount of consumed energy in the data transmission processes, primarily the data processes are divided processes in Sensor Layer and ICT Backbone Layer. When a sensor detects an event, the data would be verified preliminarily in the sensor layer. If the event is determined to be an accident, the prevalidated result would be verified again for an obvious situation, and then the accident information will be delivered to the user. In other words, normally the minimum number of sensors is turned on for sensing events, and then other sensors or surveillance systems are implemented when the accident is detected that is to save energy effectively in the monitoring system. Samanta et al. [27] suggest an efficient energy saving method for the elderly in a health monitoring system. Using the prediction algorithm, the sensor nodes are identified and stored as a sensor was often used or not from the data detected at wireless sensor nodes for 10 days because the existing elderly monitoring system consists of too many cognitive sensors including wearable sensors that wastes power usage. Based on this data, energy consumption would be lower based on this data, energy would be saved because the sensor nodes that are not used in the certain period of time would be deactivated for 2 hours after 10 days. Park et al. [28] propose a power management system, called Smart Energy Management System (SEMS) by using the ZigBee-based communications. SEMS is an energy saving method that a power socket would be turned on by using motion sensors when a user operates equipment in the vicinity the socket. The motion sensor detects user every 10 minutes. If anyone is detected, the socket turns on to use appliances. In addition, if the users are left there after using the unit, the power sockets would be turned on until next detection moment, after that the socket would be turned off. This system could reduce energy consumptions and interrupt standby powers unless the user is near the socket.
As described previously, smart home systems in terms of energy reservation are focused on how to efficiently use energy such as the smart grids, the new wireless sensor network functions, and the use of context-awareness or inference algorithm. However, it was hard to find researches and system developments of the specialized energy-saving system or method for the specific age groups, especially the elderly in smart residential environment.
3. Discussion
From the previous section, a smart home is clearly defined, and prior-arts in the cognitive sensor network-based systems for elderly smart housing are surveyed. Furthermore, energy-saving technologies based on IT in a smart home are studied. Summarizing the studies examined in the previous section are as follows:
Most of IT services for smart elderly housing are based on sensor networks targeting at one specific function such as health monitoring or fall detection or security and they are based on one type of network. Sensor network-based systems for residential environment for the elderly mainly focus on relatively narrow area such as risk detections/monitor and health-related area. Energy-saving technologies for the elderly-friendly residential environment are rarely found despite the numerous IT systems for energy saving have been proposed. Most of sensor network-based system/services for elderly housing are oriented on information technology itself as if the systems can be applicable to all types of old people, even though the elderly themselves are classified. Most of sensor-network-based services/systems for elderly housing are designed independently without considering spatial and architectural designs.
As taking into account on the summaries above, this section proposes possible cognitive wireless sensor network research directions for elderly housing in terms of converging IT into architectural design and technologies.
3.1. Adaptation and Utilization of Cognitive Radio- (CR-) Based Wireless Sensor Network for Designing Elderly Housing
As mentioned above, most of IT services for elderly housing are depending on sensor networks which exchange small detection data and focused on specific one function such as health monitoring or fall detection or security. Furthermore, the sensor networks are most likely configured in one-type of network such as wireless local area network or ZigBee or Bluetooth or cellular network; that is, the networks are not heterogeneous networks. However, elderly housing needs more sensors comparing normal people's residential area to provide more various and simultaneous services. That is, unlike services focusing only one function, the system/services need to provide various elderly cares such as health, safety, security, and convenience at the same time. Therefore, the elderly housing may be equipped with many different sensor networks which becomes heterogeneous network. In addition, unlike exchanging small data between sensors, the housing requires wireless multimedia sensor networks that deals with bulky video/image data.
In summary, the sensor network for the elderly housing can be characterized as heterogeneous and bulky data-handled condensed sensor networks. In such network environment, wireless networks' performances might be degraded because of the interferences from different types of networks. The interference comes from the fact that most of the networks for smart housing use Industry-Science-Medical (ISM) frequency band due to free of use of the channels. In particular, ZigBee or wireless personal area network or Bluetooth network which is well-used for sensor networks and uses small transmit power is fatal if the networks coexist with bulky data-based WLANs as shown in [29, 30]. Moreover, even though there is only one type of network, in a dese network environment, network performances are significantly degraded [31]. To alleviate such issues, CR-based sensor networks for elderly housing need to be considered. Because CR networks enable operating channels to dynamically change, interference and collisions from other networks can be removed, so that reliable data transmission can be achieved. However, as long as we research, the research on CR-based wireless sensor networks for elderly housing is hardly found in literatures.
3.2. Classification and Application of the Senor Network Technology from Elderly Types
Currently, residential environment designs for the elderly are changing to residential types as independent or group because of increasing the number of single elderly household in the future and are in progress to be minimized or optimized in accordance with their living types and characteristics of the elderly. On the other hand, information technologies and services used in the smart home are mostly formed to focus on the general convenience by utilizing the newest sensor or network technologies rather than designed them based on the characteristics, capabilities, and needs of the users and as a consequence, the necessity of using them is effectively reduced [6]. For example, some of the smart home technologies that are recently developed are controlled by smart phones, but they are not available technologies for the users who are not able to use or do not use a smart phone, who might be the older people. Particularly, in order to perform studies on design of the sensor network-based systems for smart the elderly's housing, the studies on the elderly themselves who have a variety of physical/active limitations need to be performed in advance. That is, prior researches such as comparative analysis of the elderly's behavior with general adults, behavior analysis based on physical types and age groups of the elderly, and requirements analysis on residential life of elderly people are required. Through doing this analyses in terms of the elderly's many aspects, sensor network-based IT services and systems based on such requirements and types of the elderly need to be clarified and classified, and then the results need to be applied and reflected to design smart homes for the elderly. As a result, it is expected that implementation of low-cost IT service and systems optimized for the elderly might be feasible.
To classify the types of the elderly, we may adapt a method used for assessing the elderly's activities of daily living (ADL). In ADL assessment, the old people are asked for their functional status such as eating, toileting, walking, and so on, and they are asked to answer one of three types: fully independent, partially dependent, and fully dependent. That is, functional status of the elderly are classified as such three types. Lim and Chung [32] try to map the three types with architectural factors (Safety, Convenience, Healthiness, and Sociality) and apply this to design the elderly's housing. An example of the mapping process is shown in Figure 5. Such similar process might be applied to build the elderly type-customized IT services/systems. IT service technologies for the elderly's housing are sorted and classified according to four architecture factor types as well as the elderly types used in ADL assessment. Therefore, IT services/systems are also packaged for the architecture factors and the elderly's types. By doing this, IT service packages specialized on the elderly activity types as well as architecture types could be applied to build the elderly's housing. As consequences, this package would easily apply IT service designs itself to residential area designs for certain elderly types, and it would be possible to design residential environments with optimizer smart home services and design cost reduction unlike conventional smart home design in which IT services are for general old people. It also reduces time-consumption and cost to design IT service/system for the elderly's housing.
Correlations between types of the elderly and architectural factors.
3.3. System Development for Preventing from Unnecessary Energy-Losses due to Physical/Mental Particularities of the Elderly
As many existing studies, reducing energy consumptions as efficiently as possible by utilizing sensors and smart devices in smart homes would be one good way for energy-savings. However, the smart home for the elderly may require more energies comparing to normal people's house because the old people need more systems and services due to their physical limitations. On the other hand, the research needs to focus on reducing unnecessary energy loss due to the elderly's physical/mental limits, which have not been well-studied so far. Therefore, the smart home for the elderly considers not only how to efficiently use the energy, but also how to reduce unnecessary wasted-energy due to the nature of limited physical and mental abilities. For example, the elderly might let home appliances continuously operate even though they are not using the appliances because the elderly easily forget to turn off them. For another example, they might operate an air conditioner or heater while windows are open. Thus, in order to reduce such energy-wasting cases, behavior patterns of the elderly with different characteristics need to be carefully scrutinized and the cases wasting energy in the elderly's house are defined. By doing this, we may develop smart IT system for saving energy specialized for the elderly. As a part of this, some IT systems might be considered as follows. The first example of the system may be a system to block abnormal energy usages comparing to the life pattern of individual old people. By collecting data of an old person's living pattern and analyzing the data, when unexpected energy is spent besides the behaviors of any particular pattern of the elderly people by times and situations, the system automatically blocks the loss of energy. For the second example, a system integrating multiple appliances which are affected each other in energy perspective is needed to block any unnecessary energy loss. This is applied to the aforementioned case like turning air conditioner with opening windows. That is, air conditioner and windows are correlated because when turning on air conditioner, windows need to be closed. Like this case, if there is correlated operation between multiple appliances, a system is needed to let those appliances cooperatively operated, so that energy loss can be automatically blocked without a physical interruptions, which are constraints in the elderly.
3.4. Convergence with the Architectural Technology
3.4.1. Architectural Design Cooperating with Sensor Network-Based Services/Systems Design
As defined above, a smart home is specialized as a designed living space for improving the performance and efficiency in various aspects with user-centered environment comparing to the traditional residential environment. Convergence of the IT technology and architecture design of the existing residential area needs to be considered for the accomplishment of smart home's purpose for the elderly. In designing a smart home for the elderly, designing sensor network-based services and systems is exclusively and separately proceeded with the area/space design and architectural design. On the other words, during the process of architecture design, design of sensor network-based IT services and systems for the elderly housing are somewhat abstractly utilized or carelessly considered. Thus, mismatching of initial designs of architect and ITs and frequent change-requirements in architectural design or IT system design during the subsequent construction process occur. As a consequence, the increase of budgets, processing-time, and inefficiency of IT systems occurs. In particular, inefficient sensor network design generates cases in which the users would not use the services.
For example, because of the exclusive operation between architectural design and IT service design, the efficient visual range of surveillance camera would not be ensured, and the design of IT systems and sensors would not be effective. In the first case, despite the problem of invasion of privacy, the use of the monitoring camera has been recognized as necessary for risk detections, and so forth in the elderly residential environment. However, to increase the number of surveillance cameras or to limit its monitoring function would be a problem by designing space and user's movement to ignore the visual range and resolution of installed camera. In the second case, even though the use of the various communication sensor modules and various wireless communication devices is increasing for the behavior judgment and context awareness of the elderly, their substantial function would not be performed by expansion of the shadowing areas due to not only communication interferences between each other [29, 30] but also inappropriate materials used for constructions of spaces.
Thus, space design as an architectural process and sensor network design as IT service/system design process need to be cooperatively progressed from residential area design from the beginning. Through this, it will be able to minimize the unnecessary waste of budget and time and to increase user's satisfaction. Even though we propose the method mentioned in this subsection for the elderly housing, this proposed idea can be applied to any other house/building design process to obtain similar benefits. However, because sensor network-based services/systems for the elderly housing need to be more optimized for the elderly comparing to universal house design [33], the proposed method is required more in the elderly's housing.
3.4.2. Convergence of Sensor Network-Based Home Services/Systems with Building Information Modeling (BIM)
As part of aforementioned cooperation between sensor network and architect designs, a method for modularizing sensor network technology and systems for elderly housing need to be studied in accordance with design modules of Building Information Modeling (BIM) that is used for architectural design. As shown in Figure 6, BIM is a simulator using data models of every object in a building as applying building's characteristics, information, and change factors that cognize each other. Moreover, it can create and manage various data applied to a variety of fields from the concept design phase to maintenance phase. Furthermore, it can store all data in computer database from the construction design and express the data to various types as occasion demands. In other words, it is a designing and processing tool that predicts and prepares constructions in advance and minimizes wastes and builds better quality of the building by creating a digital model in a virtual space with 3D model having attribute information of the object. An example of models designed by BIM is shown in Figure 7.
Building information modeling.
Architectural (a), structural (b), and plumbing (c) models of BIM for Hilton Aquarium at Atlanta, Georgia, USA [35].
BIM which recently gives many advantages to building designs is focused on the architecture, construction, electrical equipment design, and so forth; on the other hand the information about the sensor/network modules for IT system design is very limited. Accordingly, based on the classification of sensor network technologies previously proposed for the elderly, some libraries for sensor networks' components might be built in BIM, so that the housing designers will be able to easily apply such components to their elderly housing design from the beginning stage of the design process. Unlike current design process in which space design and IT system design are separated, since a space designers design housing with considering IT systems, the better and more efficient housing design for the elderly can be realized.
3.4.3. Convergence of Wireless Sensor Network Technology according to a Modular Construction Technology
Recently modular-based architecture and construction technology [33, 34] are actively being researched as an alternative residential area for the elderly. Modular architecture technology is an industrialized building construction system where modular units produced in the factory are moved to the construction site and the building is finalized by assembling them. It increases efficiency through the modularization of building materials, minimizes construction processes at site, and provides more secured works in the construction processes. Moreover, it could be moved and reusable technology even after installation. The advantages of modular construction are described as Figure 8. This modular design technology would be expected to apply residential designs for the elderly a lot. The reason is that number of the elderly who live alone will increase in the future as illustrated in Figure 3, and residential area for them will be smaller. The smaller house is needed for the elderly because it has small house works [32]. In addition, as aforementioned above, types of the elderly are changed as time goes by, and according to this, area for them will be also possible to change. Atkinson et al. [33] also insist that the modular construction-based house is appropriate for the elderly's housing because it is low cost and is reusable. In conclusion, it is certain that the modular construction technology is used for the elderly's housing.
Advantages of the modular construction technology.
Therefore, the sensor network technology according to this modular architecture should be developed to install and operate effectively within the modular residential environment. Even if the environment is formed to different shapes by another resident, the sensor network technologies enabling to provide always efficient and reliable services are necessary to be studied. As an example of this, instead of using wired sensor networks, the wireless-based sensor networks are suitable for a modular transformative residential areas. In other words, the use of the wireless sensor networks could solve the trouble caused by wires for changing areas freely, and the considerations of the line arrangement might be lower in the modular area implementation. For another example, there might be the detection and link technology of dynamic and automatic connection device in the central management panel. Eventually, the wireless sensors as mentioned above would collect data and deliver control command through the central management system (central control panel with a type of GUI). In this case, the type and location of the communication device would be changed by changing areas in various ways, and this will be automatically detected, and then the technology is necessary to be integrated and removed for sensors and devices in the central management system without user's additional behavior.
4. Conclusion
Even though many countries are heading to an aged society or even an aging society, studies on residential environment for the elderly have not actively been conducted so far. Particularly, IT services/systems represented by sensor networks for smart home are mainly focused on universal purpose, not specialized for the elderly. In this paper, we propose the directions of researches for sensor networks-based elderly housing in three perspectives. One is adopting CR-based sensor network technologies to cope with dense sensors environment and heterogeneous network environment, customizing sensors/networks classification correlated with the elderly types, and converging sensor network technologies with architectural technologies. We hope that these researches might be an initiative that the elderly-specialized smart home with IT is developed to satisfy user characteristics in the future, so that the elderly has the better life.