The document proposes an Alert Management Tool (AMT) to help caregivers monitor alerts from ambient assisted living (AAL) systems. The AMT uses an argumentative multi-agent system to generate reports explaining alerts detected by the Necesity AAL system. The AMT provides caregivers with sensor data graphs, a 3D simulation, and text explanations to help validate alerts. An example scenario shows how the AMT helps determine that an inactivity alert from Necesity was a false alarm by considering sensor data and the context that the elderly person's home was visited by an acquaintance. Future work will further integrate the AMT's interfaces and allow caregivers to query the system.

1. Andrés Muñoz, Emilio Serrano,
Juan A. Botía
{amunoz, emilioserra, juanbot}@um.es
University of Murcia
Spain
1
Ana Villa
ana.villa@ami2.net
Ambiental Intelligence &
Interaction, SLL (Ami2)
Murcia, Spain

2. Outline
 Introduction
 A Proposal of AAL System: Necesity
 Checking Alerts Through a Visual Assistant
 Argumentative MAS for the AMT
 AMT presented
 AMT Use Example
 Conclusion and Future Work
2

3. Introduction
Motivations:
 Number of people living alone is growing rapidly in
the last years (especially elderly people)
 Ambient Assited Living systems (AALs) aimed to the
monitoring of elderly people living independently
 It is necessary to develop interfaces between carers
and the AAL system
 Carers should be able to check the situations inferred by the system in a
friendly and intuitive manner
 (alerts, subject’s location and activities, etc.)
3

4. 4
Introduction
Proposal:
 We propose here an alert management tool (AMT) for
supporting the carers in their task of monitoring the
alerts detected by AAL systems
 Several types and levels of information are offered:
1. A group of graphs showing sensor data, subject’s location, etc.
2. A visual simulation in 3D, and
3. A text-based explanation

5. 5
A Proposal of AAL System: Necesity
Necesity:
 We adopt Necesity as an AAL system reference to
develop and validate our AMT
 Necesity is a non-intrusive AAL system designed to
detect domestic incidents on elderly people who live
independently
 Long inactive periods due to falls, unexpected
patterns of behaviour, etc.
 Necesity has been tested and validated in
several hundred of houses in Murcia

6. 6
A Proposal of AAL System: Necesity
 Necesity is composed of:
 A mini-computer with
wireless communication.
 Three types of wireless
sensor:
 Motion sensors (infrared) in rooms
 Pressure sensors in beds and
armchairs
 A magnetic sensor in the main
door for detecting any person
entering or leaving the house
 Sensor data are transmitted
using ZigBee technology

7. 7
Checking Alerts Through a Visual Assistant
 Carers in Necesity must decide whether an alert is a false alarm or it is
necessary to launch an emergency protocol.

8. 8
Checking Alerts Through a Visual Assistant
 We have defined a process to decide if it is necessary to
launch an emergency protocol using our AMT.
 This process relies on an argumentative MAS.

9. 9
Argumentative MAS for the AMT
 AAL systems have to face
ambiguous/inconsistent situations
 We have developed an argumentative
multi-agent system to evaluate sensor
data.
 This MAS is able to cope with
inconsistent and ambiguous situations:
 Inactive periods when the elderly is
sleeping or resting in the armchair
 Detection of different contexts when
the elderly is accompanied
 It allows us to generate reports to
explain the alerts raised by Necesity

10. 10
Argumentative MAS for the AMT
Context Layer:
• Entails simple and complex contexts
• Context agents for each subtype of
context
• Each context agent infers a specific context
and builds arguments to justify it. Then,
they send the to the Context Aggregator
agent (CAA).
• CAA uses the arguments provided to
decide which context is more plausible in
case of inconsistency.

11. 11
Argumentative MAS for the AMT
Assessment Layer:
• Evaluates contexts received from the
Context Layer and generates a report
indicating whether the occupant is in a
safe or unsafe situation.
• AssesA uses that context info,
occupant’s profile data and a set of
assessment rules to this end.
• MAS paradigm: distributed and
modular architecture which is
efficiently executed and easily extended

12. 12
AMT presented
 Sensor data logged by Necesity
is provided to our AMT which
uses the argumentative MAS to
generate a report explaining the
most plausible reason for the
alarm.
 Carer may access to more detailed
information by clicking on it in the
report window.
 Carers should validate the report
through two visual elements:
 A. Sensor Monitor Panel
 B. 3D Simulation

13. 13
AMT presented
A. Sensor Monitor Panel

14. 14
AMT presented
B. 3D Simulation

15. AMT Use Example
Scenario:
 The elderly is located sleeping in her bedroom
 At one point during the night, a relative who sometimes sleeps in the
occupant’s house enters it.
 In that moment, the sensor in the main door is activated, and subsequently
the motion sensor in the hall is activated as well.
 Next, the relative enters his bedroom, which does not have any sensors
installed in it.
 As a result, the last active location registered by Necesity is the hall.
 Since no new movement is detected in the hall afterwards, Necesity
triggers an inactivity alert several minutes later
 An unexpected lack of movement in the hall at night may indicate that the
occupant has suffered a fall or faint.
 This alert results in a false alarm since the occupant is actually sleeping
in her bedroom, which is considered a safe context
 3D simulation movie 15

16. AMT Use Example
 Conflict: Occupant is in the hall and
inactive? / there is an accompanist and
the occupant is sleeping?
 Argumentative MAS concludes the
second case -> safe situation
 How? -> five agents involved in an
argumentation
 These are the details, but our AMT
allows to study them intuitively by the
text report, the event charts and the
simulation.
16
ARGUMENTATION
 Location Context Agent (LCA): occupant’s
location in the bedroom (argument ALC2)
 SleepingCtx Agent: uses ALC2 to entail
that occupant is sleeping.
 Assessment agent (AssesA) classifies this
context as safe (sleeping in the normal
limits).
 At 02:08, LCA detects movement in the
hall, the occupant must be there
(argument ALC1)
 Context aggregator agent (CCA) detects a
conflict between ALC1 and ALC2 and
chooses ALC1 (move sensors are more
reliable).
 AccompaniedCtx Agent detects that a
person has entered the house (no
movement – door open – movement).
 CAA chooses now ALC2 over ALC1 (the
occupant’s profile says that she may be
accompanied at nights).
 AssesA classifies this context as safe and
detects a possible false alarm.

17. Conclusion and Future Work
 A fundamental aspect that must be taken into account when
designing AAL systems is the interface between carers and
these systems.
 This work is focused on the design of these interfaces
 We propose an alert management tool (AMT)
 It allows carers to interpret and validate the alarms generated in a
visual and intuitive way.
 It provides text-based explanations, sensor data graphs and 3D
simulations.
 Future steps in the development of our AMT:
 To interconnect its three interfaces
 To allow the carer to pose queries.
17

18. 18