1. Smart Home Technologies
System Engineering

2. System Engineering in Intelligent Environments
Intelligent Environments are complex systems consisting of various components
Building infrastructure
Sensor and actuator hardware
Database system
Prediction and decision making
Interaction with inhabitants
Design and construction of such systems requires a systematic approach
Precise specifications are important
System has to be treated as a whole

3. The Goals of System Engineering
Increase the probability of success
Assure that the design addresses the actual problems
Ensure that the desired design is technologically possible
Reduce risk
Assess the potential risks
Refine design to address risks
Reduce total-life-cycle cost
Reduce the likelihood of large-scale redesign

4. System Engineering
System engineering addresses the complete system as a whole
“Put software into context”
Relate software to hardware
Address work flow and other human activities
Business model
Business Process Engineering
Focus on a business enterprise
Product Engineering
Focus on a product to be built

5. System Elements
Systems generally consist of a large number of elements and processes that combine in various ways to address a given problem
Software
Hardware
People
Database
Documentation
Procedures

6. Operation, Maintenance
The System Life Cycle
Define
Requirements
Retirement,
Disposal &
Replacement
Investigate
Alternatives
Operation, Maintenance
& Evaluation
Full-Scale
Design
Integration
& Test
Implementation

7. The System Design Process

8. The vee Life-Cycle Model

9. System Engineering
System engineering is aimed at managing the system life cycle throughout the specification, design, and construction phases
In a business this has to involve management, engineering, and human factors concerns
Requires understanding of all the components that make up a system

10. Outcomes and Decisions
Systems Engineering Process
Requirements
Management Element
Plan and
Organize
Plans and Direction
Control
Analyze
Problem
Assess and Select
Outcomes and Decisions
Synthesize
Solution
Verify
Solution
Technical Element
Physical Solutions

11. Systems Engineering Process
Many steps are involved in systems engineering
Requirements engineering
System modeling
Risk analysis
System integration
Steps are not serial but rather parallel and highly iterative

12. Requirements Engineering
Requirements engineering attempts to specify a system that meets the customer’s needs and expectations.
Requirements elicitation
Requirements analysis
Specification
Modeling
Validation
Management

13. Requirements Discovery
System requirements have to be determined in collaboration with the customer
Preferences
Low energy consumption
Automatic taping of favorite TV shows
Mandatory requirements
Maintain temperature
Prevent intrusion

14. Requirements Elicitation
Eliciting requirements from customers is an important and difficult process that poses many challenges
Scope:
Defining the system boundary
Lack of clarity on overall objectives
Understanding:
Customer not skilled
Doesn’t state the obvious
Requirements ambiguous, conflicting, …
Volatility:
Requirements change over time

15. Requirements Elicitation
Requirements elicitation process:
Assess feasibility
Identify people and their roles
Define technical environment
Identify domain constraints
Select elicitation methods
Solicit participation from several perspectives
Identify ambiguous requirements
Create usage scenarios

16. Requirements Specification
Requirements specifications have to be formalized so that they can be used in the design and construction process
Elements of a Specification:
Written documents
Graphical models
Formal mathematical models
Final work product:
System Specification

17. Requirements Validation
To assure that requirements specifications can be used and will lead to good designs they have to be evaluated
Are requirements stated clearly?
Are requirements verified by an identified source?
Are requirements consistent with overall objective?
Are requirements consistent with domain constraints?
Are requirements essential to overall objective?
Are requirements bounded and unambiguous?
Are requirements conflicting with other requirements?
Are requirements sufficiently abstract?
Are requirements achievable in the technical environment?
Are requirements testable, with specified tests?
Are requirements traceable to the system model?

18. System Modeling
Once requirements are specified, systems engineering aims at forming a system model at various resolutions
At each resolution:
Define processes
Represent process behavior
List process assumptions
Define external and internal inputs
Model linkages (control, data, I/O)

19. System Modeling
System modeling identifies and defines the main aspects and specifications of the system
Assumptions
range of allowable data
Simplifications
partition data into categories
Limitations
bounds on functionality
Constraints
guide the implementation
Preferences
indicate preferred architecture (data, functions, technology)

20. System Modeling
Part of the role of system modeling is to translate the requirements specifications into a possible design and to identify potential problems
Evaluate the system’s components in relation to one another
Link requirements to system components
Validate assumptions about data flow, work flow, input / output, ...

21. Risk Management
Risk assessment and management identifies and assesses different risks in the development process and of the product
Product risk
Product performance
Reliability of home access
Consistency of AC system
Cost of door authentication system
Project risk
Cost, schedule and process performance
Duration of the technology development
Cost of production
Safety and environmental risk
Risks to the public
Reliability of outdoor robots

22. Risk Management
Risk management in industrial practice is a tradeoff between costs and risks
“Good risk management will not prevent bad things from happening. But when bad things happen, good risk management will have anticipated them and will reduce their negative effects”

23. System Engineering in Risk-Prone Environments
At NASA, the probability of mission failure was about 10-2, but the severity was near 1. The product of these numbers was big, so they did lots of systems engineering.
At a big software house, the probability that a new system will destroy user files was about 1, but their perceived severity was around They did not care if J.Q. Public lost a few files. Therefore, they did little systems engineering.

24. Construction And Integration
The construction phase attempts to take the models and specifications and translate them into a product
Construction focuses on the details
Implementation of individual elements
Goals:
Implement the architectures and infrastructure
Integrate and deploy the completed system

25. Requirements Management
Assurance of conformity of models and constructed products with the requirements is an important part of system engineering
Active throughout the life-cycle
Identify, control, and track:
New requirements
Changes to requirements
Tools:
Traceability Table
Relates requirements to features, source, dependency, subsystem, interface, etc.

26. System Engineering Tasks

27. Conclusions
System engineering is important for the successful construction of large scale systems
Assure requirements are specified correctly
Engineers and scientists do not necessarily know what inhabitants of intelligent environments really need
Model the system to assess feasibility
Often intended features are not feasible or too costly
The self-regulating home is not (yet) technologically possible
Assess economic viability
To make intelligent environments reality they have to be economical and fit the requirements of users
Assess project risks and track requirements
Economic as well as physical risks to inhabitants have to be taken into account to field a system
A good engineer in intelligent environments has to have some understanding of all aspects of system engineering