In this demo, we present an assembly of silver assistants for supporting Aging-In-Place (AIP). The virtual agents are designed to serve around the clock to complement human care within the intelligent home environment. Residing in different platforms with ubiquitous access, the agents collaboratively provide holistic care to the elderly users. The demonstration is shown in a 3-D virtual home replicating a typical 5-room apartment in Singapore. Sensory inputs are stored in a knowledge base named Situation Awareness Model (SAM). Therefore, the capabilities of the agents can always be extended by expanding the knowledge defined in SAM. Using the simulation system, we can rapidly conduct various types of experiments to test and evaluate whether the silver assistants have effectively and reliably fulfilled their duties when serving the elderly.NRF (Natl Research Foundation, S’pore)Accepted versio

KANG, Yilin

SUBAGDJA, Budhitama

TAN, Ah-hwee

WANG, Di

English

Wang, Di

Subagdja, Budhitama

Kang, Yilin

Tan, Ah-Hwee

DR-NTU (Digital Repository of NTU)

Silver assistants for aging-in-place

Institutional Knowledge at Singapore Management University

Singapore Management University Institutional Knowledge at Singapore Management University Research Collection School Of Information Systems School of Information Systems 12-2015 Silver assistants for aging-in-place Di WANG Budhitama SUBAGDJA Yilin KANG Ah-hwee TAN Singapore Management University, ahtan@smu.edu.sg Follow this and additional works at: https://ink.library.smu.edu.sg/sis_research  Part of the Artificial Intelligence and Robotics Commons, and the Databases and Information Systems Commons Citation 1 This Conference Proceeding Article is brought to you for free and open access by the School of Information Systems at Institutional Knowledge at Singapore Management University. It has been accepted for inclusion in Research Collection School Of Information Systems by an authorized administrator of Institutional Knowledge at Singapore Management University. For more information, please email cherylds@smu.edu.sg. Silver Assistants for Aging-In-PlaceDi Wang†, Budhitama Subagdja†, Yilin Kang† and Ah-Hwee Tan‡†Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly and ‡School of Computer EngineeringNanyang Technological University, 50 Nanyang Avenue, Singapore 639798Email: {wangdi, budhitama, ylkang, asahtan}@ntu.edu.sgAbstract—In this demo, we present an assembly of silverassistants for supporting Aging-In-Place (AIP). The virtual agentsare designed to serve around the clock to complement human carewithin the intelligent home environment. Residing in differentplatforms with ubiquitous access, the agents collaboratively pro-vide holistic care to the elderly users. The demonstration is shownin a 3-D virtual home replicating a typical 5-room apartment inSingapore. Sensory inputs are stored in a knowledge base namedSituation Awareness Model (SAM). Therefore, the capabilities ofthe agents can always be extended by expanding the knowledgedefined in SAM. Using the simulation system, we can rapidlyconduct various types of experiments to test and evaluate whetherthe silver assistants have effectively and reliably fulfilled theirduties when serving the elderly.I. INTRODUCTIONThe world’s population is aging and nowadays more elderlychoose to live in their own homes as long as possible. Tosupport their independence and to ensure their safety, varioustypes of technologies have been developed to meet the rapidlyincreasing needs for Aging-In-Place (AIP). Such technologiesinclude smart home applications, reminder systems, medica-tion adherence assistance, anomaly detection, etc. These tech-nologies are extensively studied in the specific domains. How-ever, they may not be easily extended and be readily integratedwith the others. In this paper, we present an assembly of silverassistants who provide holistic elderly care with ubiquitousaccess. These virtual agents have their own specialties whilesharing a common knowledge base named Situation AwarenessModel (SAM). As such, the capabilities of the agents canalways be extended by expanding the knowledge defined inSAM. For demonstration purpose, SAM receives simulatedsensory inputs from a 3-D virtual environment, which repli-cates a typical 5-room apartment in Singapore. In the virtualhome, we can either control manually or automatically witha script, the behavior of the 3-D avatar (elderly occupant)performing various Activities of Daily Living (ADLs). Mean-while, the changes in the environment are reflected in SAM inreal-time. Based on the sensed context in SAM, the agentsdecide whether the elderly occupant requires any specificassistance or general companionship. The agents can providea broad range of assistance, reminders, recommendations, andcompanionship for physical, cognitive, emotional, social, andsustainability supports [1]. To promote a healthier lifestyle, theagents would try to convince the elderly [2] if they do not showinterests in certain recommendations. Moreover, to enable theagents to collaborate with maximum efficiency and minimummisunderstanding, we define a coordination proxy [3] for themto communicate with the others. The overall system frameworkis illustrated in Fig. 1 and the details are elaborated in thefollowing section.Fig. 1. The overall system framework of silver assistants for aging-in-place.II. SILVER ASSISTANTS FOR AGING-IN-PLACEThe purpose of the silver assistants is to provide holisticcare. They serve the elderly in various ADLs and interactwith the concerned parties for general updates and reports ofanomaly. For example, if the system detects a fall [4] and doesnot receive a positive response from the elderly within certaintime, the agents will alert the emergency contact immediately.Currently, we have developed two silver assistants for demon-stration, namely smart butler and virtual nurse.The smart butler (see Fig. 2b) resides in mobile devicessuch as a smartphone (which has a high penetration rate of 83%among senior Singaporeans in 2012), which are constantlycarried around by the owners. The butler, as its name sug-gests, provides all-round tender care through frequent naturalinteractions (speech and taps). Its context panel displays the pe-ripheral information. It provides various types of applicationsvia the respective buttons in the function panel being pressed.Most importantly, the interaction panel delivers all types ofmessages (reminders, recommendations, small talks, etc.) andlearns the user response by identifying the respective responsebutton being pressed. More details can be found in [1], [5].The virtual nurse (see Fig. 2c) resides in the home com-puter [1]. Again, as its name suggests, the nurse specializes inhealthcare: promoting healthy lifestyles and providing healthrelated recommendations to the elderly. It naturally interactswith the elderly through speech and mouse clicks and its mostunique features include the use of a computational model foradaptive persuasion. More details can be found in [1], [2].The agents can only make sensible decisions if they arefully aware of the situation. Therefore, we use SAM to store allthe real-time collected sensory inputs and to make inferences.There are mainly four types of situational attributes defined inSAM: (1) Inputs from home-installed sensors1 (e.g., ON/OFF1Another team in our research centre is currently working on how to reflectthe changes sensed in the real-world inside the virtual environment.Fig. 2. An exemplar scenario wherein the two agents collaboratively encourage the elderly occupant to do some physical stretches after the Situation AwarenessModel infers that she has been sitting on the sofa for too long.switches, RFID trackers, acoustical sensors, etc.); (2) Inputsfrom mobile sensors (e.g., motion [6], mood [5], heart ratefrom smart-watch, etc.); (3) Online activities (e.g., activitieson social network services, news crawled online, etc.); and(4) Inferred context (e.g., few phone calls lately, sitting fortoo long, etc.). SAM is designed in such a way that all thesensory inputs can be collected in the real-world environment.For demonstration and experimental purposes, a 3-D virtualworld (see Fig. 2a) is implemented to simulate a real-worldindoor living environment, wherein the situation is capturedand reflected in real-time by the situational attributes in SAM.In this demo, we develop a number of scenarios to simulatevarious activities of the elderly occupant in a day.III. DEMONSTRATION SCENARIOSOur demonstration scenarios serve to illustrate the fivemain types of care provided by the silver assistants [1],which are presented as follows: (1) Physical care, such as falldetection and encouragement for exercise; (2) Cognitive care,such as medication adherence and reminder for unattendedstove; (3) Emotional care, such as greetings, conversations, andmusic selection; (4) Social care, such as event recommendationand suggestion for social contact; and (5) Sustainability care,such as suggestions for energy-saving and phone-charging.Due to the page restriction, we only present one selectedscenario2.In the illustrated scenario (see Fig. 2), SAM sensed thatthe elderly occupant had been sitting on the sofa for toolong and subsequently updated the respective inferred context.Both the smart butler and virtual nurse noticed the updatedcontext and wanted to suggest some physical stretches. Beforeinteracting with the elderly, the agents communicated throughthe coordination proxy and agreed that the smart butler wouldinitiate the conversation. However, when the elderly occupantwas reluctant to follow the advice, the butler asked the nursefor support. The nurse agreed with the butler and persuaded theoccupant in a personalized manner according to her motivationand responses [2]. At last, the elderly occupant recognized thebenefits and agreed to the suggestion of physical exercise. Insummary, this demonstration scenario shows: (1) Interactions2The presentation slides prepared for the demonstrations are availableonline: https://www.dropbox.com/s/51zqbzksoq9mf3j/SA4AIP.pdf?dl=0among the two agents and the human user; (2) Collaborationbetween the agents; and (3) Adaptive persuasion.IV. CONCLUSION AND FUTURE WORKIn this paper, we present a framework for supportingaging-in-place, consisting of an assembly of silver assistantsand a virtual environment simulating a typical apartment inSingapore. Through various demonstration scenarios coveringthe physical, cognitive, emotional, social, and sustainability as-pects, we show how the overall system achieves the objectivesas designed. For future work, we will conduct experiments toevaluate the effectiveness of the agents by simulating differentbehaviors of the elderly occupants. In addition, we aim toenhance the representation of knowledge in SAM so that usersmay define new rules and the rules can further be learned andtuned adaptively through interactions.ACKNOWLEDGMENTWe thank our colleagues Kah-Hoe Pang, Huiguo Zhangand Jun Ji for sharing an earlier version of the 3-D virtualhome. This research is supported by the National ResearchFoundation, Prime Minister’s Office, Singapore under its IDMFutures Funding Initiative and administered by the Interactiveand Digital Media Programme Office.REFERENCES[1] D. Wang, B. Subagdja, Y. Kang, A.-H. Tan, and D. Zhang, “Towardsintelligent caring agents for aging-in-place: Issues and challenges,” inProceedings of IEEE Symposiumon on Computational Intelligence forHuman-Like Intelligence, 2014, pp. 1–8.[2] Y. Kang, A.-H. Tan, and C. Miao, “An adaptive computational model forpersonalized persuasion,” in Proceedings of International Joint Confer-ence on Artificial Intelligence, 2015, pp. 61–67.[3] B. Subagdja and A.-H. Tan, “On coordinating pervasive persuasiveagents,” in Proceedings of International Conference on AutonomousAgents and Multiagent Systems, 2014, pp. 1467–1468.[4] J. Dai, X. Bai, Z. Yang, Z. Shen, and D. Xuan, “Mobile phone-basedpervasive fall detection,” Personal and Ubiquitous Computing, vol. 14,no. 7, pp. 633–643, 2010.[5] D. Wang and A.-H. Tan, “Mobile humanoid agent with mood awarenessfor elderly care,” in Proceedings of International Joint Conference onNeural Networks, 2014, pp. 1549–1556.[6] D. Wang, A.-H. Tan, and D. Zhang, “Non-intrusive robust human activityrecognition for diverse age groups,” in Proceedings of IEEE/WIC/ACMInternational Conferences on Web Intelligence and Intelligent AgentTechnology, 2015, p. to appear.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6482&context=sis_research

Silver assistants for aging-in-place

Abstract

Similar works

Full text

Available Versions

DR-NTU (Digital Repository of NTU)

Institutional Knowledge at Singapore Management University