Wireless Sensor Networks for the Determination Wellness of Elderly People by Designing of a Multi-Sensor Based System by Experimental Studies

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1 Wireless Sensor Networks for the Determination Wellness of Elderly People by Designing of a Multi-Sensor Based System by Experimental Studies K.Srinivasa Reddy, Research Scholar,Bharath University,Chennai, India, Associate Professor, Department of Electronics and Communication Engineering, Nagole Institute Of Technology And Science, Hyderabad, Telangana, India. Abstract The proportion of elderly people in any population is growing rapidly creating the need to increase geriatric care and this trend isn t going to change in the near future. This will put tremendous strain on national resources and the cost of elder care is only going to escalate. More and more elderly people are choosing to stay alone, independently, rather than in a retirement village or old people s home. Such people, often frail and infirm, do however require constant monitoring so that medical help can be provided immediately in times of dire needs. Considerable research efforts have been focused towards in-home monitoring of elderly people, often using wireless personal area networks. As wireless sensing technology continues to evolve, it is playing an important role in improving the quality of life for elderly people and their families. Wireless sensors based smart home monitoring system provides a safe, sound and secure living environment for the elderly people. A wireless sensors based smart home consists of number of wireless sensors that provide information. The information from the sensors can be used for monitoring elderly people by detecting their abnormal patterns in their daily activities and picking up any unforeseen abnormal condition when occurs. The project is focused on research and developmental issues of an intelligent wireless sensors based smart home and determination of person s daily activities based on the usage of different appliances. The daily pattern can then be compared to determine the early signs of behavioral pattern change of elderly, which can potentially allow for early medical intervention. While several sensors are readily available off the shelf, making them intelligent in the context of a specific application (such as monitoring of the elderly) is always a challenging task. We have developed a framework, dealing with the design intricacies and implementation issues of novel sensors, targeted to achieve a Digital Home specifically for the elderly. The developed monitoring system is used to recognize activities of daily living and life style of elderly person living alone. Even though the monitoring system uses a limited number of sensors, it determines the daily behavior of the person. The system was installed in residential environments with ease. Moreover, the proposed sensing system presents an alternative to sensors that are perceived by most people as invasive such as cameras and microphones, making the sensors are almost invisible to the user thereby increasing the acceptance level to use the system in a household environment. Keywords: Wsn, Zigbee, Sensor, Hearbeat Sensor. I. OVERVIEW OF THE SYSTEM Wireless sensor network for wellness determination of elderly involves functional assessment of daily activities and health monitoring of elderly in this A smart sensor coordinator collects data from the sensing units and forward to the computer system for data processing. Collected sensor data are of low level information containing only status of the sensor as active or inactive and identity of the sensor. To sense the activity behavior of elderly in real time, the next level software module will analyze the collected data by following an intelligent mechanism at various level of data abstraction based on time and sequence behavior of sensor usage. II. EXISTING SYSTEM Home Monitoring Activities through camera lacks a huge acceptability among elder persons. Other than camera, infrared small motion detectors, passing sensors, operation detectors and IR motion sensors have been incorporated in the house for monitoring human activity behavior and the interpretation of human activity is limited only to a few human activities. There are many existing systems on personal wellness monitoring and safety like RFID Communication technology and wearable health devices integrated with sensors to provide continuous monitoring of person s health related issues and activity monitoring. RFID (Radio Frequency Identification) is the abbreviation for individual identification by radio waves. The system is able to collect positional information when a radio wave transmitted by an RFID reader strikes an RFID tag with embedded information, which is then included in the radio wave reflected to and captured by the reader. Though these devices are for specific purposes they have severe concerns related to security, privacy and legal aspects. Usually people are reluctant to wear a system continuously Available Online@ 251

2 on their body. So it may not be viable option for a healthy elderly people. This situation may be acceptable for a patient under rehabilitation. Wireless sensor networks offer a number of advantages over traditional RFID implementations, First of all, the ability to rapidly deploy a multi-hop network (RFID is single hop only) allows WSNs to be used in a number of ad hoc/temporary. WSN is ability to locally store data when the tag/node is 'out of network' and then download that data when the tag or node comes back into a network provides an audit trail with time line, environmental conditions and location. Using wireless sensor network it is possible to monitor elder person who is alone at home, using Zigbee module. III. PROPOSED SYSTEM In the present work, an intelligent home monitoring system based on ZIGBEE wireless sensors networks has been designed and developed to monitor the and evaluate the well being of the elderly living alone in a home environment. Wellness of elderly can be evaluated for forecasting the unsafe situations during monitoring of regular activities At the low level module wireless sensor network integrated with ZIGBEE modules of mesh structure exists capturing the sensor data based on the usage of electrical appliances and stores data in the computer system for further data processing Collected sensor data are of low level information containing only status of the sensor as active or inactive and identity of the sensor The low level module consists of a number of sensors interconnected to detect usage of electrical devices, bed usage and chairs etc. ZIGBEE transceiver which communicates at 2.4 GHz (ISM) through radio frequency protocols and provides sensor information that can be used to monitor the daily activities of an elderly person Using wireless sensor network it is possible to monitor elder person who is alone at home, using Zigbee module and GSM module. IV. NEED FOR EARLY DETECTION OF AGEING CHANGES/PROBLEMS OF ELDERLY PEOPLE The increase ageing of population in the world is associated with the increase of suffering with many disabilities. So there is a need for an in-home pervasive network which assists and helps the residents by controlling home appliances, medical data look back and also communicating in case of an emergency. Too often are headlines such as these seen in the paper: Elderly man lay dead for days, and Woman found starved in flat. It is shocking to know that no one was looking after these people and imagine they must have an uncaring family. At the same time however, as a society we value our rights to live independently and keep control of our own lives. Many dread the thought of being forced to live with their adult children, or in a rest home or other sheltered living arrangement yet at the same time they know there is a high risk of death because of a collapse, a fall, or stroke. There are many people in our community who because of age or some infirmity, or perhaps because their memory and judgment can no longer be totally relied upon, are having pressure put on them by loving relatives to leave their home and give up their precious independence. Any abnormal events which can occur to an old person in a home often leads to more serious illnesses or even death. But in a case of reduced mobility or other factors which leads to this kind of situation should also be considered for effective monitoring, which will make a significant impact on the health of the elderly people. Surely, with the technology of today, there is a better way for these people to resolve this problem. This technological assistance or monitoring of a person in the home is achieved using few but effective wireless sensors, which are centralized in structure and distributed around the house. The smart home concept is a promising way to improve the living standards of elderly by improving the home care for the elderly. The smart home monitoring can circumvent institutionalizing the older persons and can help them live at home in safety and provide independence. The smart homes target to improve comfort, quality of life, safety, monitoring, monitoring mobility and physiological parameters. Modern sensor not only assists and monitors people with reduced physical functions but helps to resolve the social isolation they face. They are capable of providing assistance without limiting or disturbing the resident s daily routine, giving him or her greater comfort, pleasure, and well-being. A number of smart homes have now been developed around the world by many institutes and researchers. The smart home is based on smart and intelligent sensors, which are developed, fabricated and configured around a wireless network. It is expected that these smart homes can reduce escalating medical costs. V. OUR APPROACH AND SOLUTION Recent advances in sensor technology, communication systems, and information technologies have created ample opportunities to develop novel tools enabling remote monitoring in-case of emergency conditions, and to care the elderly. In-home monitoring has the added benefit of evaluating individualized health status and reporting it to care providers, and caregivers alike; allowing timelier and individually targeted preventive interventions [13]. The smart homes equipped with the wireless sensor networks will benefit both health care providers and their patients. By monitoring the patient continuously and reporting any abnormal situation, the system frees human labour and thus reducing labour costs and increasing efficiency by notifying doctors or health care provider quickly. The data collected from various sensors over the network in a smart home can be stored and integrated into comprehensive health record. Other issues Available Online@ 252

3 like quality of life for elder people, such as privacy, independence, dignity and convenience are supported and enhanced by the ability to provide services in the patient s own home. It is a known fact that the use and the way of implementation of wireless sensor networks drastically change from one application to other application; the need for in-depth study on performance parameters is vital. While several sensors are readily available off the shelf, making them intelligent in the context of a specific application (such as monitoring of the elderly) is always a challenging task. For example, an intelligent wireless sensor system will not only detect the usage pattern of the daily appliances, it will have capabilities to collate the data and analyse them. Depending on the data analysis it can detect any abnormality. To achieve this I have developed and implemented a SMART component-based system by integrating various sensors and communicating via standard radio frequency protocols. The system depends on a set of selected number of wireless sensors and controller which relies on inputs from sensors. This system will consist of a proof-of-concept that what I have developed is feasible, reliable, practical and scalable. Figure 2: code execution using visual basic VI. RESULTLS Below figure shows Integration of all sensors with ARM7 this is connected to the Zigbee and GSM modules, for monitoring the person and controlling. Figure 3: Entering the port number for execution of code Below screenshot shows display of temperature and heart beat rate of elder person who is alone at home Figure 1: Integration of all sensors with ARM7 These sensors are connected to the ARM7 board by using GSM and ZIGBEE modules we can monitor the person who is alone at home, we can also control some operations such as if the temperature is high we will be getting message to our mobiles through GSM module then we can on fan, and if the light intensity is less then we can switch on light, if the heart beat rate is more then we will be getting message to the mobile then we can admit that person into hospital. Figure 4: Temperature And Heart Beat Rate Display Conclusion In the present work, an intelligent home monitoring system based on ZIGBEE wireless sensors networks has been designed and developed to monitor the and evaluate the well being of the elderly living alone in a home environment. To sense the activity behavior of elderly in real time, connect all Available Online@ 253

4 the sensors to particular person then these sensors collect the data and the next level software module will analyze the collected data by following an intelligent mechanism at various level of data abstraction Based on time and sequence behavior of sensor usage and pass it through the network to a main location. For knowing wellness of the person up to date, here we are using Zigbee and GSM modules for passing information about the elder person to the monitoring person, if the temperature or heartbeat rate of the elder person is exceeds particular value then it will send a message to the monitoring person so that he can act further. This thesis has undertaken a fundamental study to develop an in-house sensing system based on wireless sensor networks to monitor elderly. The wireless elderly monitoring system demonstrates that smart, simple sensor devices can be used to recognize activities of daily living and life style of elderly person living alone. The system is becoming more complete as more intelligent features are added to detect the daily activity patterns efficiently. Even though it uses a limited number of sensors, it can capture the abnormality in a person s daily routine by recognizing the use of appliances necessary for daily living, thus determining the life style of elderly person living alone. The system can be installed/ maintained in residential environments without any complexity. Moreover, the proposed sensing system presents an alternative to sensors that are perceived by most people as invasive such as use of cameras and microphones, making the sensors are almost invisible to the user thereby increasing the acceptance level to use the system in a house hold environment. The system can be easily installed in an existing home environment with no major modifications or damage.the developed system continuously monitor the activity of the elderly person staying alone and generate the sensor activity pattern to analyze and foresee the changes in daily activities of the elderly person. In the near future, the generated activity pattern related to weekdays and weekends will be used to predict the unusual behavior of the elderly person based on the classification model of regular and irregular sensor activity. Results of Real-time activity behavior recognition of the inhabitant were encouraging. Classification of abnormal situation based on multi-level check method was validated with machine learning methods. Integration of wellness function in the developed software system was effectively able to determine the abnormal situation of the inhabitant. A. GSM Modem: A GSM modem is a wireless modem that works with a GSM wireless network. A wireless modem behaves like a dial-up modem. The main difference between them is that a dial-up modem sends and receives data through a fixed telephone line while a wireless modem sends and receives data through radio waves. A GSM modem can be an external device or a PC Card / PCMCIA Card. Typically, an external GSM modem is connected to a computer through a serial cable or a USB cable. A GSM modem in the form of a PC Card / PCMCIA Card is designed for use with a laptop computer. It should be inserted into one of the PC Card / PCMCIA Card slots of a laptop computer. Like a GSM mobile phone, a GSM modem requires a SIM card from a wireless carrier in order to operate. As mentioned in earlier sections of this SMS tutorial, computers use AT commands to control modems. Both GSM modems and dial-up modems support a common set of standard AT commands. You can use a GSM modem just like a dial-up modem Figure 5: GSM In addition to the standard AT commands, GSM modems support an extended set of AT commands. These extended AT commands are defined in the GSM standards. With the extended AT commands, you can do things like: Reading, writing and deleting SMS messages. Sending SMS messages. Monitoring the signal strength. Monitoring the charging status and charge level of the battery. Reading, writing and searching phone book entries. The number of SMS messages that can be processed by a GSM modem per minute is very low, only about six to ten SMS messages per minute. B. Operation And Results Wireless sensor network for wellness determination of elderly is working with sensors includes heart beat sensor, temperature sensor, LDR sensor, MEMS sensor, and Driver unit which is connected to two external devices such as fan and light. Sensors sense the respected values and send it to the ARM7 processor, that will be processed and send it to the Zigbee module and GSM module, while coding we will set particular value to the temperature sensor, heart beat sensor, LDR sensor, MEMS sensor, when it exceeds that particular value then we will be getting message to our mobile through GSM module. Available Online@ 254

5 Figure 6: Integration of all sensors with ARM7 CONCLUSION In this system, the required number of sensors for monitoring the daily activities of the elderly have been used. A smart sensor coordinator collects data from the sensing units and forward to the computer system for data processing. Collected sensor data are of low level information containing only status of the sensor as active or inactive and identity of the sensor. To sense the activity behavior of elderly in real time, the next level software module will analyze the collected data by following an intelligent mechanism at various level of data abstraction based on time and sequence behavior of sensor usage. Acknowledgment The author would like to thank Mr.K.Srinivasa Reddy, Associate Professor, for providing necessary facilities to carry out this work. A special gratitude to my parents for their constant encouragement without which this assignment would not be possible. References [1] A. H. Nasution and S. Emmanuel, Intelligent video surveillance for monitoring elderly in home environments, in Proc. IEEE 9th Workshop Multimedia Signal Process., Oct. 2007, pp [2] Z. Zhongna, D. Wenqing, J. Eggert, J. T. Giger, J. Keller, M. Rantz,and H. Zhihai, A real-time system for in-home activity monitoring of elders, in Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., Sep. 2009,pp IEEE SENSORS JOURNAL, VOL. 12, NO. 6, JUNE 2012[3] S. J. Hyuk, L. Boreom, and S. P. Kwang, Detection of abnormal living patterns for elderly living alone using support vector data description, IEEE Trans. Inf. Technol. Biomed., vol. 15, no. 3, pp , May [4] A. Wood, J. Stankovic, G. Virone, L. Selavo, H. Zhimin, C. Qiuhua,D. Thao, W. Yafeng, F. Lei, and R. Stoleru, Context-aware wireless sensor networks for assisted living and residential monitoring, IEEE Netw., vol. 22, no. 4, pp , Jul. Aug [5] J. K. Wu, L. Dong, and W. Xiao, Real-time physical activity classification and tracking using wearble sensors, in Proc. 6th Int. Conf. Inf.,Commun. Signal Process., Dec. 2007, pp [6] Z. Bing, Health care applications based on ZigBee standard, in Proc.Int. Conf. Comput. Design Appl., vol. 1. Jun. 2010, pp. V1-605 V [7] K. P. Hung, G. Tao, X. Wenwei, P. P. Palmes, Z. Jian, W. L. Ng, W.T. Chee, and H. C. Nguyen, Context-aware middleware for pervasive elderly homecare, IEEE J. Sel. Areas Commun., vol. 27, no. 4, pp , May [8] H. Yu-Jin, K. Ig-Jae, C. A. Sang, and K. Hyoung-Gon, Activity recognition using wearable sensors for elder care, in Proc. 2 nd Int. Conf. Future Generat. Commun. Netw., vol. 2. Dec. 2008, pp [9] A. A. Moshaddique and K. Kyung-Sup, Social issues in wireless sensor networks with healthcare perspective, Int. Arab J. Inf. Technol., vol. 8,no. 1, pp , Jan [10] K. Hara, T. Omori, and R. Ueno, Detection of unusual human behaviour in intelligent house, in Proc. 12th IEEE Workshop Neural Netw. Signal Process., Nov. 2002, pp [11] S.-W. Lee, Y.-J. Kim, G.-S. Lee, B.-O. Cho, and N.-H. Lee, A remote behavioral monitoring system for elders living alone, in Proc. Int. Conf.Control, Autom. Syst., Oct. 2007, pp Authors: Mr.K. Srinivasa Reddy is research scholar from bharath university,chennai and also Associate Professor of the Electronics and Communication Engineering, Nagole Institute of Technology and Science, Hyderabad.He received his B.Tech degree in Electronics and Communication Engineering from JNT University, Hyderabad, and M.Tech degree in Embedded Systems from JNT University, Hyderabad.. He is a member of The International Association of Engineers (IAENG). He had twelve publications in National and International Journals. He has written three text books in the field of wireless communications. Available Online@ 255