UNIVERSITY OF GUYANA

A SENTIENT APPROACH TO DESIGNING SMART DEVICES

A Thesis

Submitted to the Department of Computer Science

Faculty of Natural Sciences

UNIVERSITY OF GUYANA

in partial fulfillment of

the requirements for the

degree of

Bachelor of Computer Science

Department of Computer Science

by

Christopher Clarke

July 2017

ii

UNIVERSITY OF GUYANA

FACULTY OF NATURAL SCIENCES

DEPARTMENT OF COMPUTER SCIENCE

THESIS PANEL

________________________________

Andreasa Morris-Martin, Msc.

Secondary Supervisor

________________________________

________________________________

___________________________________

Roland Daynauth, Msc.

Primary Advisor

Student: Christopher Clarke

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ACKNOWLEDGEMENTS

I extend credit to my advisor and professors for providing me with guidance and insight to complete

this project.

To my family and friends for their unwavering support and encouragement, thank you.

To my peers and to the persons who took time from their day to participate in the evaluation, many

thanks.

Christopher Clarke

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ABSTRACT

The rapid increase in the processing capabilities of computing devices has led to several endeavours

into Artificial Intelligence technology in the form of Natural language interfaces & Assistants i.e

Siri, Cortana, Google Assistant etc. However, when applied to the concept of designing a true

‘smart’ device this approach results in a notable disconnect between the device and its associated

source of ‘intelligence’.

We propose that this restricts the range of the behaviour and depth of intelligence of the device in

question. Utilizing an intelligent agent approach and the notion of sentience, this paper proposes a

new design philosophy to designing smart devices. One where the device itself is aware of its

purpose and has the ability to perceive its environment (encompassing organization, identification

& interpretation), act on the perceived information and continually learn in desire of fulfilling its

true process.

Keywords: sentient, intelligent agents, smart devices, sentient object model, context awareness,

intelligent personal assistants, autonomy, rationality.

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TABLE OF CONTENTS

THESISPANEL..........................................................................................................................ii

Acknowledgements................................................................................................................iii

ABSTRACT..............................................................................................................................iv

LISTOFTABLES.......................................................................................................................vi

Chapter1.Introduction..........................................................................................................61.1ResearchBackground...................................................................................................................61.2Thesisoutline...............................................................................................................................8

CHAPTER2.BACKGROUND......................................................................................................92.1SmartDefinition..........................................................................................................................9

CHAPTER3.METHEDOLoGY..................................................................................................143.1FRAMEWORKFUNDAMENTALPILLARS......................................................................................143.2HOWITWORKS.........................................................................................................................15

3.2.1PurposeDeclaration/Extraction.................................................................................................15

3.2.2PerformanceMeasureIdentification.........................................................................................16

3.2.3DescriptionofEnvironmentProperties......................................................................................17

3.3EVALUATION..............................................................................................................................18

CHAPTER4.IMPLEMENTATION.............................................................................................20

5.EVALUATION.....................................................................................................................245.1Results.......................................................................................................................................24

6.conclusion.........................................................................................................................266.1FutureWork..............................................................................................................................26

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LIST OF TABLES

Table4.1–SecurityPEASDescription.........................................................................................................22

Table4.2–ComfortPEASDescription........................................................................................................22

Table4.3–AccommodationPEASDescription...........................................................................................22

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LIST OF FIGURES

Figure 2.1 – Sentient Object Model ............................................................................................... 10

Figure 2.2 – SOME Land Platform ................................................................................................ 11

Figure 2.3 - The Hello.Wall ........................................................................................................... 12

Figure 2.4 – Smart Skin Model ...................................................................................................... 13

Figure 3.1 – Sentient Object Model Extraction Process ................................................................ 14

Figure 3.2 – Example of stage 1 on Smart Home .......................................................................... 16

Figure 3.3 – Example of stage 3 on Smart Home .......................................................................... 18

Figure 4.1 Stage 1 – Purpose Extraction of smart home ................................................................ 20

Figure 4.2 Stage 2 –Performance Measure Identification of smart home ..................................... 21

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CHAPTER 1. INTRODUCTION

The field of Artificial Intelligence seeks to build intelligent machines. Some researchers equate

this achievement to that of thinking and acting in the same manner as a human being. Others

see it as thinking and acting in a rational manner (Russel & Norvig, 2010). Despite whichever

side, research on Artificial Intelligence is growing at an unprecedentedly rapid pace. “Accenture

research on the impact of Artificial Intelligence in 12 developed economies reveals that AI

could double annual economic growth rates in 2035 by changing the nature of work and creating

a new relationship between man and machine” (Purdy & Daugherty, 2016). As such Artificial

Intelligence is quickly making its presence known in the areas of business, medical sciences,

robotics etc. just to name a few, and its impact can no longer be ignored. Further Evidence of

this is shown in the projection that “AI bots will power 85% of customer service interactions

by 2020” (Tonner, 2016). Artificial Intelligence is being planted into just about anything you

can think of and with the rapidly growing processing power capabilities & the Internet of things;

just about every object we interact with and depend on will embedded with some form of

intelligence. These devices/objects are often referred to as smart devices. The most prevalent

example of this is the rising popularity of intelligent digital assistants such as Apple’s Siri,

Microsoft’s Cortana, Google Now and Amazon’s Alexa. While different in their own individual

rights, each of these digital assistants sit as a natural language interfaces on a specific device

and uses forms of speech recognition to understand voice commands and query their pool of

knowledge to provide the user with a response/action. However, there is notable disconnect

between the device itself and its associated source of ‘intelligence’. Do these assistants fulfill

the true purpose of the devices they are placed on? If were are to design a truly smart device

should it be embedded with its own source of intelligence and be designed in a manner that it

works to fulfill its defined purpose? Or does the path of deploying an intelligent personal

assistant suffice in achieving this goal? This paper seeks to propose a new design philosophy

to designing smart devices. One where the device itself is aware of its purpose and has the

ability to perceive its environment (encompassing organization, identification & interpretation)

in desire of fulfilling its true process.

1.1 Research Background

Artificial Intelligence defined by (McCarthy, 2007) is the science & engineering of making

intelligent machines. As computers’ ability to perform a variety of tasks in a short amount of

time continues to grow, the question arises of how may a device or software think intelligently?

“No one can refute a computer’s ability to process logic. But to many it is unknown if a machine

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can think.” (Smith, McGuire, Huang, & Yang, 2006). Several attempts have been made to

emulate human intelligence in devices:

• Deep Blue, IBM’s chess playing super computer who defeated Chess Grand Master

Garry Kasparov in the late 1990’s (Hintze, 2016).

• Experts Systems were developed to deal with theorems proof, geometric problems and

chess playing (Smith, McGuire, Huang, & Yang, 2006).

• Self-driving cars embedded with representations of the outer world capable of

navigating the outside environment.

• Smart homes with automated security systems & control centers.

• Intelligent personal assistants capable of scheduling meetings & booking reservations.

All of these applications & devices express some form of human intelligence or in the very least

automate a task previously carried out by a human. Such applications fall into the category of

Reactive AI machines & Limited Memory AI machines. Reactive AI’s on one hand simply

perceive their environment directly & acts on what it sees. It forms no memories or past

experiences to further utilize in current or future decisions (Hintze, 2016). Limited Memory

AI’s on the other hand contain a pool of preprogrammed representations of the world & utilize

them to make decisions based on the sensed input (Hintze, 2016). All of of these advancements

have led to to utilization of AI in business, medicine, robotics etc. (Russel & Norvig, 2010) and

to the expectation that AI will “unleash remarkable benefits across countries, countering dismal

economic growth prospects and redefining “the new normal” as a period of high and long-

lasting economic growth” (Purdy & Daugherty, 2016).

Leading the charge in the Artificial Intelligence boom are IPA’s (Intelligent Personal

Assistants). (Garrido, Martinez, & Guetl, 2010) define these Intelligent Personal Assistants as

“software agents which assist users in performing specific tasks. They should be able to

communicate, cooperate, discuss, and guide people.” These Intelligent Agents “are autonomous

entities provided with an initial knowledge and with the capability of learning to achieve their

goals”. This allows the IPA to adapt to rapidly changing environments thus reducing work &

information reload (Garrido, Martinez, & Guetl, 2010). It is projected that these digital

assistants will know humans personally by 2018 (Tonner, 2016) and that “by 2019 virtual

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assistants will account for 20% of all smartphone interactions” (Gartner, 2016). The most

common & popular form of the person assistant are the ones embedded into today’s

smartphones (MacManus, 2016). Siri, Google Assistant, Cortana are just a popular few among

the vast list of personal assistant software emerging every day. These IPA’s sit as interfaces on

top of their specific devices and interact with the user through speech recognition & natural

language processing. They are able “to (at least to some extend) understand and respond to

spoken inputs, to a somewhat broader end-user level” (Milhorat, et al., 2014).

All using their own individual methods & approaches these examples have made advances in

allowing to machines to portray forms of intelligence. However, if we are to extend further into

Artificial Intelligence, shouldn’t the design of our devices follow suit? This research

emphasizes on the concept of smart devices and its composition. It then describes a framework

for modeling the design for a device deemed intelligent.

1.2 Thesis outline

This thesis documents the formulation of a new design approach to designing smart devices. It

starts by outlining the background to the research in Chapter 1. In this chapter it gives a brief

background to the problem encompassing the aims and objectives. In chapter 2, literature is

reviewed pertaining to the topic. Chapter 3, makes mention of the methodology used in

obtaining the results. While, Chapter 4 describes the implementation of the model in practice

and chapter 5 produces the results and findings obtained from the previous chapter. Finally,

Chapter 6 gives recommendations and discussion of the developed models, as well as, future

work and limitations to the study.

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CHAPTER 2. BACKGROUND

Researchers and product designers have developed a series of devices falling into the category

of ‘smart’. These range from smart watches, smart televisions and even smart fridges. This

research focuses on the conceptualization phase of the product design of such devices using a

sentient approach.

2.1 Smart Definition

The Oxford dictionary defines the term smart as “having or showing a quick-witted

intelligence”. (Russel & Norvig, 2010) apply what they call a Rational Agent Approach to

defining intelligence. In this approach the agent is expected the do more than just act. It operates

autonomously, perceives its environment, persists over a prolonged time period, adapts to

change, and create and pursues goals. Such an approach is advantageous because of its

generality compared to the “laws of thought” approach and it is considered more amendable to

scientific development and research compared to approaches of human behavior and human

thought (Russel & Norvig, 2010). As such it is imperative device falling into this category of

‘smart’ carry out these agent functionalities. We define this capability as being sentient.

Presented below is a comprehensive, but not definitive, summary of previous related work

which will establish the scope of this research.

(Fitzpatrick, Biegel, Clarke, & Cahill, 2002) define a sentient object as a mobile, intelligent

software component that is able to sense its environment via sensors and react to sensed

information via actuators. The authors developed what they call the Sentient Object Model and

provided concrete definitions for the terms sensor, actuator and sentient object [see fig 2.1].

Integral to this model is the characteristic of contextual awareness in which they elaborated on

the three sub-sections of contextual awareness: Context Acquisition, Context Representation &

Inference. (Fitzpatrick, Biegel, Clarke, & Cahill, 2002) were able to model the expected

behavior of a sentient object when it interfaces with an another sentient object or the external

environment.

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Figure 2.1 – Sentient Object Model

(Mazzei, Montelisciani, & Fantoni, 2014) argued that the low customizability of standard mass

market products, gadgets and things in general, leads to the perception of obsolescence and lack

of appeal, drawing comparison between the smart phone and our standard everyday objects.

They identified that the modern day smart phone deploys what they call the “Operating System

paradigm” that allows users to customize their devices with services (apps) convenient to them.

The Operating System (OS) thus “acts as an enabling platform for the customization process of

physical devices by means of an almost unlimited set of bricks selectable by the average user”

(Mazzei, Montelisciani, & Fantoni, 2014). As such (Mazzei, Montelisciani, & Fantoni, 2014)

developed a platform for smart object design [see fig 2.2] that enabled person’s to customize

appearances, structure, functionality and behavior of the device. However, the platform mostly

catered for the creation of simple reactive devices that do not require contextual awareness and

does not provide the creator with a framework for identifying the essential requirements of their

desired device.

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Figure 2.2 – SOME Land Platform

(Streitz, et al., 2005) introduced the notion of “smart environments”. These are environments

that “integrate information, communication, and sensing technologies into everyday objects”

(Streitz, et al., 2005). They attributed the realization of this notion to the increasing

miniaturization of everyday devices and to the fact that researchers have augmented the

standard functionality of everyday objects to create smart artifacts constituting an environment

that supports a new quality of interaction and behavior.

In their research (Streitz, et al., 2005) distinguished between categories of smart devices:

system-oriented, importunate smartness and people-oriented, empowering smartness. System

oriented devices stimulates an environment in which the device itself or the environment in

question is capable of taking action based on prior information collected. In contrast, people-

oriented devices leave the decisions up to the end user. This follows the principle that “smart

spaces make people smarter” and empower them. The system mines and compiles data from

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the environment and disseminates this information in a digestible form so the end user can

comprehend and determine future actions. From this (Streitz, et al., 2005) developed the

Hello.Wall [see fig 2.3]. The Hello.Wall constitutes a seeding element of a social architectural

space conveying awareness information and atmospheres in organizations or at specific places

in an attempt to be a smart artifact that users can communicate with in a simple and intuitive

manner. They focused primarily on designing the experience of interacting with devices in the

given environment opposed to the internal composition of the device and its intelligence.

Figure 2.3 - The Hello.Wall

(Chen & Chiu, 2005) examined the emerging smart home and the possibilities of it being a part

of everyday life. Smart homes are defined as “a residence equipped with computing and

information technology which anticipates and responds to the needs of the occupants, working

to promote their comfort, convenience, security and entertainment through the management of

technology within the home and connections to the world beyond” (Chen & Chiu, 2005).

Seeking to solve the question as to why & how the devices of the home would

interact/communicate with other objects, the users and the enabling environment, (Chen &

Chiu, 2005) proposed an agent based approach. Using their own modified version of Russell &

Norvig’s PEAS description [see Fig 2.4] and the agent environment model, Chen & Chiu

designed a feasible model for the Smart Skin. This skin “works as an environmental awareness

agent which is capable of “flexible” autonomous actions, including reactivity, pro-activeness

and social ability.” (Chen & Chiu, 2005). Upon receiving sensor information from the device

the smart skin triggers one of a set of defined actions.

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Figure 2.4 – Smart Skin Model

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CHAPTER 3. METHEDOLOGY

THE SENIENT OBJECT MODEL THEORETHICAL FRAMEWORK AND

METHODOLOGY

Figure 3.1 – Sentient Object Model Extraction Process

Fig 3.1 represents a high level overview of the underlying processes carried out by the

framework. The designer is carried through a three (3) stage “filtration process” whereby a set

of key questions are answered in order to extract the necessary elements required to implement

the desired intelligence of the device.

As output the designer is presented with a design specification detailing the necessary

components required to design a device true to the operational definition of “smart”. The

specification should describe a sentient system capable of acting rationally towards a set of

purpose specific goals.

3.1 FRAMEWORK FUNDAMENTAL PILLARS

The underlying processes carried out by this theoretical framework are grounded on research

theory in disciplines of Agent Based Computing, Ubiquitous Computing and select spectrums

of artificial intelligence such as intelligent agents etc. Fundamental to the design of the sentient

object model are the following characteristics:

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• Purpose Driven – in order to define a well refined scope for the device’s sentience the

sentient focuses on the fundamental purpose of the device.

• Autonomy - this implies the device “operates without the direct intervention of humans

or others, and has some kind of control over their actions and internal state”

(Castelfranchi, 1995). This covers both reactive & pro-active autonomy, allowing our

object to have complete independence and act without needing interactions from the

user or another entity.

• Contextual Awareness – “Essentially sentient objects sense and interact with their

environment via sensors and actuators. It is this awareness of, and interaction with the

environment that makes context awareness an important factor in sentient objects.”

(Fitzpatrick, Biegel, Clarke, & Cahill, 2002)

• Rationality – A rational agent is expected to do the right thing in a given situation. “The

object agent will act in order to achieve its goals, and will not act in such a way as to

prevent its goals being achieved.” (Galliers, 1988b)

3.2 HOW IT WORKS

The model consists of three (3) major phases:

i. Purpose declaration/extraction

ii. Performance Measure Identification - using the work of (Russel & Norvig, 2010)’s

rational agent approach as the basis.

iii. Description of Environment Properties – using the work of (Russel & Norvig, 2010)’s

PEAS description as the basis.

3.2.1 Purpose Declaration/Extraction

Integral to the process of identifying necessary components of the device is the derivation of

the devices true underlying purpose. The term sentient in its truest form is defined as “the ability

to perceive and feel things”. Sentient computing further abstracts this as the ability to use

sensors to perceive the environment and react appropriately. By identifying the underlying

purpose of the device we are better able derive the components necessary to achieve the desired

sentience and its forms a basis for the device’s embedded knowledge and hardware design.

Since the characteristic of perception & rationality is key, a series of questions are asked to

identify the underlying purpose of the device.

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Key Questions

i. What is the true purpose of the device?

ii. If this object were alive, what would be its purpose?’

These questions are designed to abstract purpose from the device in the context of it being alive

and conscious. This is useful as the designer has the liberty of extracting the core purpose of

the device from the standpoint of it being an actual sentient being. This can result in the

identification of a series of identified purposes (1..n) nodes/entities.

Figure 3.2 – Example of stage 1 on Smart Home

3.2.2 Performance Measure Identification

For each of the identified purposes extracted in stage 1, the process of performance measure

identification is carried out. In this stage the designer seeks to identify the primary focus of the

purpose at hand. When the specific entity/node is placed into its environment, a series of actions

are carried out based on what it perceives from the outer environment or other sentient artifacts.

If the series of actions are desirable of the designer, then the entity has performed well. This

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notion of desirability is captured by a performance measure that evaluates any given sequence

of environment states (Russel & Norvig, 2010).

Key Questions

i. What should be the focus of this identified purpose?

ii. What are the vital qualities of the identified purpose?

iii. What is the performance measure to which we would like to aspire?

These questions identify the measures by which the designer will evaluate the performance of

the identified purpose. The designer keeps in mind that it is better to design performance

measures according to what one actually wants in the environment, rather than according to

how one thinks the device should behave (Russel & Norvig, 2010). This is necessary to ensure

that our device is acting in a rational manner.

3.2.3 Description of Environment Properties

For each identified purpose in stage 1 the designer gives a thorough description of its

environments properties/task environment (PEAS). In order to ensure the rationality of the

desired device we thoroughly identify the performance measures, the devices environment, the

actuators and sensors. (Russel & Norvig, 2010) called this description the PEAS description

and it is the first step in the designing of intelligent agents. In stage 2 we described the

performance measure for each the extracted purposes. We utilize this to further extract the other

properties of the PEAS description.

Key Questions

i. What is the environment this purpose will face?

ii. What information is required to fulfill this defined purpose?

iii. Is it possible to capture such information? If so, how?

iv. Upon receipt of the information, what will be your response?

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By identifying the external environment and required information, we set the basis for the

contextual awareness of the device. From this we can extract what are the necessary sensors

required to capture this information and the necessary actuators to carry out tasks based on

sensed information.

Figure 3.3 – Example of stage 3 on Smart Home

3.3 EVALUATION

The Sentient Object Model proposed in this paper seeks to design devices true to the definition

of smart. It takes on a new design philosophy applying the concept of intelligent agents and

sentience into the way we look and design modern day devices. To evaluate this approach, we

pose the question of “if a device is truly smart, what should it be able to do?”. These

characteristics were identified in our model:

i. Autonomous

ii. Contextually Aware

iii. Rationality

Ideally to fully evaluate each of these characteristics a full implementation of the sentient device

would be necessary to conduct testing of each category. However, due to the time period

available a full implementation of the design specification produced for a device from the model

is not possible.

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To combat this, we will conduct an analysis of the design specification produced by our model

based on the outlined principles of smart established in the study. To measure each of the

necessary characteristics the following questions were asked:

• Autonomy

a) Is the device designed to make decisions based on its percepts or prior

knowledge?

b) Is the device designed for of continually learning?

• Contextual Awareness

a) Is the device capable of perceiving its environment?

b) Is the device capable of understanding perceived information?

c) Is the device capable of acting upon the perceived information?

• Rationality

a) Does the device achieve the best outcome when a change in the environment is

occurs?

b) Does the device pursue goals?

Autonomy

“To the extent that an agent relies on the prior knowledge of its designer rather than on its own

percepts, we say that the agent lacks autonomy” (Russel & Norvig, 2010). Over time it is

imperative that our device evolves. After sufficient time inside of an environment our device’s

behavior should more or less be independent of prior embedded knowledge.

Contextual Awareness

Contextual awareness is the “use of context to provide information, to a sentient object, which

may be used in its interactions with other sentient objects, and/or the fulfillment of its goals”

(Fitzpatrick, Biegel, Clarke, & Cahill, 2002). Necessary to achieve this is the ability to acquire

context (sensors), understand context (knowledge) & and act on sensed information (actuators).

Rationality

Our device should act to achieve the best outcome or, when there is uncertainty, the best

expected outcome (Russel & Norvig, 2010).

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CHAPTER 4. IMPLEMENTATION

The sentient object model was implemented to design a smart home. A smart home was selected

to test the frameworks capability of presenting a design approach for complex structures that

encompass a wide variety of variations.

Produced from the smart home implementation was the following:

Figure 4.1 Stage 1 – Purpose Extraction of smart home

Stage 1 extracted three (3) main purposes of the smart home:

• Managing security of the home

• Providing accommodation for residents of the home

• Providing comfort for inhabitants

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Figure 4.2 Stage 2 –Performance Measure Identification of smart home

In stage 2 we extracted the performance measures of the identified purposes by focusing on

what are the vital features required to achieve the said purpose and by focusing on what the

purpose should aspire to achieve.

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ENVIRONMENT PROPERTY PEAS DESCRIPTION

Performance Measures Spatial Awareness, Self-preservation,

Authorized user access

Environment People, weather, animals

Actuators Alarm, display, sprinklers, windows, doors

Sensors Cameras, Motion detectors, smoke detector

Table 4.1 – Security PEAS Description

ENVIRONMENT PROPERTY PEAS DESCRIPTION

Performance Measures Optimal temperature, Noise control, Lighting

Control

Environment Weather, People, animals

Actuators Windows, Doors, thermostat, lights

Sensors Cameras, Motion detectors, thermometer,

light sensor

Table 4.2 – Comfort PEAS Description

ENVIRONMENT PROPERTY PEAS DESCRIPTION

Performance Measures Spatial awareness

Environment People, animals

Actuators Windows, Doors

Sensors Cameras, Motion detectors

Table 4.3 – Accommodation PEAS Description

In stage 3 the designer provided PEAS descriptions for each of the defined purposes thus

outlining the devices environment, its actuators and its sensors.

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At first glance, it is apparent that the framework, even as an early prototype, proves to be

useful in provides insights into the device design and presents actionable content for

engineers and designers to utilize.

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5. EVALUATION

The evaluation was done using a simple analysis based on the fundamentals principles outlined

in theory for the characters of a device hold the title of “smart”.

• Autonomy

a) Is the device designed to make decisions based on its percepts or prior

knowledge?

b) Is the device designed for of continually learning?

• Contextual Awareness

a) Is the device capable of perceiving its environment?

b) Is the device capable of understanding perceived information?

c) Is the device capable of acting upon the perceived information?

• Rationality

a) Does the device achieve the best outcome when a change in the environment is

occurs?

b) Does the device pursue goals?

5.1 Results

Autonomy

i. The sentient home design facilitates the device making decisions based on sensed

information as well as that from prior knowledge. Sensed weather information from the

environment is used to make decisions in the facilitation of the comfort purpose. Prior

knowledge is used to in the security specification as a knowledge bank of authorized

persons needs to be kept.

ii. The sentient home shows the capability for continually learning through the

performance measure of optimal temperature. Different home types as well as user types

have preferences for temperature control. Over time the comfort agent will learn its

user’s desired temperature levels.

Contextual Awareness

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i. For each of the identified purposes, the necessary sensors required for the device to

perceive its environment were identified.

ii. The inference engine/contextual representation of the perceived information is left for

the implementation stage of the design specification. However, by identifying the the

necessary information required for the realization of the device’s purpose; the designer

is exposed to the thought of what form the sensed information shall come in and how

they will represent it.

iii. For each of the identified purposes, the necessary actuators required for the device to

act on perceived were identified.

Rationality

i. The devices’ reaction to sensed input will rely on the implemented reference engine

during the building stage. However, by identifying the performance measure the

designer is better able to anticipate what the best outcome to a trigged event would be.

ii. For each of the identified purposes, performance measures that the device should pursue

were identified.

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6. CONCLUSION

The sentient object model represents a novel effort to incorporate agent based design and

sentience into the architecture of a smart device.

Based on our evaluation, we find that the sentient object model has potential to simplify the

complexity associated with the design of devices requiring a form of intelligence. While the use

of intelligent agents has some scope, by embedding the device itself with its source of

intelligence and designing it to facilitate this, new dimensions are opened for deeper learning.

However, due to the mention limitation of time, our results may not exhibit the full spectrum

of use cases.

Nevertheless, there is conclusive evidence that there is merit to designing a smart device using

our sentient approach. Also this research can be further refined to design an even more complete

model taking the designer even deeper into the associated intelligence of the device.

6.1 Future Work

• Future work involves a full implementation and evaluation of a device specification

produced from the sentient object model.

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