A Gap Analysis Framework of IoT-empowered City Platform as a Service

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A Gap Analysis Framework of
IoT-empowered City Platform as a Service
ICSSSM2017, Dalian, China
Toshihiko Yamakami
IoT Business Unit, ACCESS
Toshihiko.Yamakami@access-company.com
2017/06
Toshihiko Yamakami (ACCESS Confidential)A Gap Analysis Framework of IoT-empowered City Platform as a Service2017/06 1 / 21

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Outline
Background
Related Work
Research Method
Gap Analysis
Gap Exposure Pattern
Gap Influence Model
Explicit Gap Logging Approach
Gap Index Flow View Model
Examples of Questionnaires
Discussion
Advantages of the Proposed Model
Limitations
Conclusion

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Background
Research Purpose
The aim of this research is to identify a methodological framework of
gap analysis of city-scale information systems.
Backgrounds
Complexity of hardware, software, integration, deployment and
operation leverages exposure to gaps at launch.
A systematic methodology to deal with these gaps in the context of
multi-faceted design challenges has been relatively unexplored.
We are engaged in CPaaS.io: City Platform as a Service and anticipate
this design gap issue.
Gaps were considered in the past as flaws, however, they are
unavoidable components in the viewpoint of complexity of IoT with
spatial and temporal dimensions.

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Related Studies and Research Method
Related Studies
a) heterogeneity of city-scale systems:impact of geographic contexts
[Mashhadi16], heterogeneous stakeholders [Yonezawa16], challenges of
multiple stakeholders of IoT [Fok11] gap between device-oriented and
data-oriented [Busemann12], architecture to accommodate
heterogeneous IoT[Shaikh16]
b) personalization and requirements gathering for special needs:
personalization of IoT [Henka16], requirement gathering of IoT with
special needs [Ferati16], Personalized IoT infrastructure
[Rothenpieler14], a personalized body sensor network [Kang16]
c) challenges of IoT in city-scale systems:DevOps in an urban area
[Moore16], a framework of assisted living [Bhattasali16]
The originality of this paper lies in identification of a framework of gap
analysis of IoT services in their design stages
Research Method:
Identifying gap patterns in a city platform from design to deployment
Identifying a flow model to construct a set of weights for each question
to formulate a gap measure, and
Identifying gap detection questions for each pattern

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Overview of CPaaS.io
Smart City Innovation is the goal of the CPaaS.io joint R&D project
between Europe and Japan starting from 2016.
To achieve this, the CPaaS.io platform combines the capabilities of
the Internet of Things (IoT), big data analytics and cloud service
provisioning with Open Government Data and Linked Data
approaches.
CPaaS.io hosts multiple projects in different cities in Europe and
Japan, e.g. Utrecht, Amsterdam, Tokyo, Sapporo, and Yokosuka.
URL: https://cpaas.bfh.ch/ CPaaS.io – City Platform as a Service

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Gap exposure patterns between design and service launch
Aspect Description
Lack of motivation End users lack the motivation to use.
Obstacles End users encounter too many obstacles to go though
and are discouraged to use.
Lack of function Capabilities of installed hardware, networks, and infras-
tructure do not reach the threshold of user satisfaction.
Instability Quality of service or availability is unstable and occa-
sional faults and problems discourage end users.
Contradiction to use
patterns
Use of systems contradict the existing daily pattern of
usage.
Lack of minimum
usage
Lack of minimum active usage discourage social adop-
tion.
Social contradiction Use of systems do not match the existing social norms
and social power relationship.
Operational burdens Maintenance of service operation requires too much re-
source.
Lack of business op-
portunities
The underlying business opportunities do not fit the
expected business model.

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Four different gap source patterns
Source pattern Description
Design Gap tendency brought by design factors.
Realization Gap tendency brought by realization factors (hardware,
software, platform, and integration)
Deployment Gap tendency brought by deployment and operation.
Adoption Gap tendency brought by adoption.

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Four directions of gap-filling in IoT design with Gap Awareness
Direction Description
People People are the direction that deals with this paper. Gap is ne-
glected due to deployment-specific factors. Building blocks to
visualize gap among diverse IoT services are considered in the pro-
posed framework.
Service Service is one future direction that will fill the gap of current
diverse IoT services. It is still too early that services will cover
deployment details of IoT.
Thing Thing is a natural direction that people pay attention to fill the
gaps. The tight dependency on things, locations, and other
facility-specific factor is still working to enlarge the perceived gaps
at the current landscape.
Business Business is another future direction that will fill the gap of IoT
services. It is one step beyond the service direction and too early
to be a tool to fill the gap.

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A gap influence model in design.
Gap

-
U
Consistency

Inconsistency

Conflicts

R
Unification
Migration,
Adaptation
Modification,
Compromises
Resistance,
Technological silos

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Two approaches towards gaps in IoT systems.
Approach Description
Implicit approach Gaps are treated as flaws. Gaps are enclosed in different
methodologies and not shared in the long-term.
Explicit approach Gaps are treated as intrinsic components of IoT systems.
They are explicitly logged and analyzed in a long-term
and multi-disciplinary method
Considering complexity and heterogeneity of IoT systems, the explicit
approach should be more encouraged.

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A classification of gap
Domain Region Description
User-use Expectation gap There is a gap between user expectation of IoT services and UIs provided by services.
This gap is enlarged when the new IoT devices are deployed and users have imaginary
expectation of advantages of installed devices.
Usability gap There is a gap between usability of hardware and software of IoT services and UIs
provided by services.
Familiarity gap There is a gap between the new way of use of IoT and the existing user methods to
deal with the problems.
Privacy context
gap
There is a gap between the privacy context which a user sets before use and the
actual use scenes.
Provider-use Operation gap There is a gap between the before-IoT operation and after-IoT operation. Also,
there is a gap between operation requirements in the pre-deployment phases and in
the post-deployment phase.
Deployment gap There is a gap between the deployment context in design stages and in post-
deployment phase. Also, there is a gap in technology landscape between in design
stages and in post-deployment phase.
Heterogeneity
gap
There is a variety of intensity of technological deployment in IoT, which provides a
spatial gap among locations of IoT deployment.
Development Transition gap There is a time gap among locations of IoT deployment, which causes transition gaps.
Also, this transition gap may appear in intra-enterprise contexts and trans-enterprise
contexts.
Integration gap There is a gap among systems and services when multiple systems and services are
integrated under a single platform.
Design Requirement
gap
There is a requirement gap among stake-holders.
Intention gap There is an intention gap among stakeholders about their goals to deploy a city
service platform.

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Gap Similarity Capturing Framework
Assessment of
perception
R
Aggregation of
dimensional rates

Composition
of a gap index
- Awareness of
gap between cases

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Flow View Model for Gap Index
Build
questionnaire
for each
domain
-
Collect
answers and
self-rated
gaps
-
Calculate
weights for
self rated
gaps
-
Use the weights
for unrated
questionnaire
results

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Examples of questions
Domain Region Questions
User-use Expectation
gap
Is there any support for building straight-forward expectation of IoT-deployed environment
for naive users?.
Is there any support for guiding naive users to build a healthy expectation of advantages
and limitations of IoT deployment?
Is there any method to detect over-hype of end users?
Usability gap Is the usability of end user device well-studied and well-designed?
Is there any support to detect and fill usability gap of the end user devices?
Is there any support for usability improvement of installation and configuration?
Are the end user devices are configurable to improve usability ?
Familiarity
gap
Is there any support to bridge the past experience and newly created experience?
Is there any support of experience transfer from the non-IoT deployed environment to the
newly-deployed environment?
Privacy con-
text gap
.Is the new privacy context involving new IoT services comprehensive to naive users?
At the time of privacy-setup, is it easy for naive users to consider the future context for
the privacy setup?
Provider-
use
Operation
gap
.Is there any support for smooth transition from the previous operation style and the newly
deployed operation style?
Deployment
gap
.Is the new deployment of devices required for the IoT services are comprehensively easy
for operation staff?
Heterogeneity
gap
Is there any gap for each IoT service end users in the multiple IoT-installed context?
Development Hardware gap Is there any gap for software development team to be filled in the newly deployed hardware
?
Integration
gap
.Is there any design gap in integration of multiple IoT services?
Design Requirement
gap
Is there any requirement gap of IoT in design?
Intention gap Is there any intention gap of IoT service deployment in any stakeholder?

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Advantages of the Proposed Approach
IoT services require intensive attention of different expert skills of hardware,
software, deployment, integration, and operation. This challenge brings
technological silos where each service design is isolated from other services.
In the existing methods, design gaps are identified as flaws. They are
identified as irregularity and dealt with in an ad hoc manner. It is necessary
to anticipate gaps in the early stage of design.
The author proposes a gap estimation method to construct proactive gap
assessment using feedback of standard questionnaires The proposed method
is a stepping stone to resolve obstacles of the silos that separate each IoT
service.

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Comparison of checklists with existing methods.
Method Comparison
Ad hoc comparison Ad hoc comparison is intuitive and easy to
focus differences. It is biased to feelings and
perceptions.
Lesson-based compari-
son
When there is a good past lesson, it is power-
ful. When there are no similar lessons learned,
it is not applicable.
Component-level com-
parison
Component-level comparison leads to super-
ficial differences. It is not good at finding
middle grounds.
Gap-model-level com-
parison (the proposed
method)
It systematically guides awareness toward
gaps among IoT services. It is usable for de-
sign collaboration.

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Approach Comparison
Approach Evaluation
Flaw reduction
approach
Poor. Complexity of IoT is difficult to manage the existing
software development methodology because it deals with
open systems including the real-world.
Guess-based ad
hoc approach
Fair. Guess-based ad hoc evaluation is misleading and
difficult to capture emerging gaps derived by new tech-
nologies.
Lesson-based ap-
proach
Fair. The lessons are valuable, however, it can be applied
to similar contexts. It is difficult to be leveraged in brand
new contexts.
Gap assessment
index based ap-
proach
Good. It is a rough scale for the starting point. Using the
quantitative learning from examples, it can be polished as
a quantitative evaluation tool.

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Three Applications
First, the proposed approach can be a starting point of gap analysis of IoT
services. It serves as a checklist to proactively examine the possible holes in
requirement realization in design phases.
Second, the proposed approach provides a theoretical framework to capture
the similarity of different dimensions of IoT design. The gap patterns can be
collected in multiple IoT services. Then, analysis of given quantitative values
provide an approximated similarity from the viewpoint of gap.
Third, the proposed method can provide a framework to capture a gap index
from the answers of gap-related questions.

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Limitations
This paper is qualitative and exploratory. Detailed analysis of case
studies in the real world is not covered in this paper. The strict
definition of each dimension and applicability to cross-service
comparison are not covered in this paper.
The proposed method provides a theoretical framework of gap
similarity analysis. The actual decision of weights of real world
examples remains for future study. Detailed analysis between
underlying assumptions, gaps, the causes of gap remain for future
study.
The quantitative advantages brought by the proposed methods are
not covered in this paper. Organizational and social aspects are
beyond the scope of this paper.

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Conclusion
The increased complexity of hardware, software, network, middleware,
deployment and operation require a systematic methodology to deal
with this less explored field of IoT software engineering.
The author proposes the explicit approach to deal with gaps in a
positive and cross-project manner. It is based on the assumption that
zero-gap is a kind of illusion in the IoT process.
Then, the author presents a gap similarity analysis to deal with the
multidisciplinary aspects of IoT inter-service comparison. Then, the
author proposes a list of questions to identify gaps at the early stage
of IoT system design. The proposal of a method deriving a
quantitative gap measure is an important building block toward
improvement of life-cycle management of IoT systems.
The future work includes verification of a measurement generation
process as well as evaluating usefulness of a gap measure from
questionnaires.

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Thank you for your attention!
Questions?

A Gap Analysis Framework of IoT-empowered City Platform as a Service

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