Application and Integration of Intelligent Systems in e-Cities

1. Application and Integration of Intelligent Systems in e-Cities Prof. A.KaklauskasResearch Institute of Internet and Intelligent Technologies, Vilnius Gediminas Technical University, Lithuania, e-mail: Arturas.Kaklauskas@st.vtu.lt

2. Technological innovation mainly through changes in the availability of information and communication technology inclusive databases of best practices, neural networks, decision support and expert systems, etc. that have been provided by a variety of new services developed by the e-cities.

6. Automation Applications • Energy Simulation, • Load Calculation, • Renewable Energy, • Retrofit Analysis, • Sustainability/Green Buildings, • Atmospheric Pollution, • Energy Economics, • Indoor Air Quality, • Multibuilding Facilities, • Solar/Climate Analysis, • Training, • Utility Evaluation, • Validation Tools, • Ventilation/Airflow, • Water Conservation, • Misc. Applications.

7. Sustainability/Green Buildings

8. Indoor Air Quality

9. Energy Simulation

10. The Database of the Best Practice • Today information technologies are rapidly expanding throughout all spheres of activities. Large amounts of information is stored and databases are created on the basis of which thousands of high quality experts pass on their experiences and expertise through the Internet. • The database of the best practice can be formed by studying the expertise of advanced industrial economies. Simulation can be undertaken to provide insight into creating an effective database of the best practices: • Alternatives of environment (a peaceful, cultural society; safe, pollution free, green environment; surroundings, public transport); • Alternatives of safety/security. • Alternatives of social cohesion (ecologically sound, economically efficient and socially cohesive settlements, caring society, no poverty); • Alternatives of quality of life (more comfort, time, money; happy people, more pleasure, less work, reconstruction of settlement structure, revitalisation of street spaces, confidence), etc.

11. Stakeholders and the Efficiency of Alternatives Stakeholders (urban planners, city administrators, elected representatives, architects, public or corporate owners of flats, etc.) decisions can increase or decrease the efficiency of alternatives. The developed intelligent systems should integrate multiple points of view and make possible the collaboration of the different stakeholders that are involved in this process.

12. Real estate agents perform a number of functions: • advising sellers on how to make the house more marketable, • assessing current market conditions, • assisting with paperwork, • negotiating the sale price, • steering their clients through the array of tasks that must be done before settlement. • For providing these services to buyers and sellers, real estate agents typically charge a commission on the sale, which by custom averages around 6 percent.

13. Under the traditional system, the real estate agent offers a package of services: • showing homes, • providing information about home values and neighborhoods, • matching buyers and sellers, • negotiating and signing the contract, • arranging for inspections, • assisting with closings, and so on.

14. Technology can disaggregate those services: • Internet searches for listings, • databases displaying home values, • smart software for boilerplate contract language, • personalized websites that manage the complicated transaction, and so on—and allow consumers to pay for only those that they want.

15. Research directions: • Search of real estate. • Finding out of alternatives and making of comparative tables. • Providing information about real estate, their values and neighbourhoods. • Matching buyers and sellers. • Negotiating the sale price. • Assistance with real estate selection. • Lender selection • Alternatives multiple criteria analysis (calculation of market value, etc.). • The after-purchase evaluation stage.

16. Framework 5 and 6 Programmes • Framework 5. Promoting Innovation in Construction Industry SMEs • (CONSTRINNONET). Contract IPS 2000-00002. CONSTRINNONET is a construction related innovation project whose objective is to find instruments that best increase the input-output ratio of RTD in the sector. • Framework 6. INTELCITIES (Intelligent Cities). The main objective of INTELCITIES is to create a new and innovative set of interoperable e-government services to meet the needs of both citizens and businesses. This will provide interactive citywide on-line applications and services for users that will make all aspects of what is “going-on” in the city available to all. • Framework 6. Bringing Retrofit Innovation to Application in Public Buildings (BRITA in PuBs). The BRITA proposal on Eco-buildings aims to increase the market penetration of innovative and effective retrofit solutions to improve energy efficiency and implement renewables, with moderate additional costs.

17. DECISION SUPPORT SYSTEM AS DEVELOPED BY THE VILNIUS GEDIMINAS TECHNICAL UNIVERSITY Based on the analysis of existing information, neural networks, expert, decision support and other systems and in order to determine best practice and to prepare recommendations for stakeholders under consideration different Decision Support Systems were developed.

18. Decision Support Web-Based Systemswere developed by VGTUconsisting of: • database of best practices, • database management system, • model-base, • model-base management system, • user interface.

19. Databaseof best practice • The presentation of information needed for decision-making in the data base of best practice may be in a conceptual form (i.e. digital/numerical, textual, graphical, diagrams, graphs and drawing, etc), photographic, sound, video and quantitative forms. • The presentation of quantitative information involves criteria systems and subsystems, units of measurement, values and initial weights that fully define the provided variants. • In this way, the DSS enables the decision-maker to receive various conceptual and quantitative information from a database and a model-base allowing him/her to analyse the above factors and to form an efficient solution.

20. The presentation of information needed for decision-making in the DSS may be in a photographic form

21. The presentation of information needed for decision-making in the DSS may be in a textual form

22. The presentation of quantitative information in the DSS

23. The following databases of best practice have been developed: • Innovation, • Construction, • Facilities Management, • Real Estate, • Refurbishment, • Sustainable Development, • Loans, • International Trade, • Ethics.

24. Innovation database

25. Construction database

26. Facilities Management database

27. The following tables form the FM’s database: •   Initial data tables. These contain information about the facilities (i.e. building, complexes, alternative facilities management organisations). • Tables assessing facilities management solutions. These contain quantitative and conceptual information about alternative facilities management solutions: space management, administrative management, technical management and management of other services, complex facilities management, market, competitors, suppliers, contractors, renovation of walls, windows, roof, etc.

28. Real Estate database

29. Refurbishment database

30. Sustainable Development database

31. International trade database

32. Ethics database

33. Model-Base • The efficiency of alternatives is often determined by taking into account many factors. These factors include an account of the economic, technical, technological, management, organisation, legal, social and other factors. The model-base of a decision support system should include models that enable a decision-maker to do a comprehensive analysis of the available variants and to make a proper choice. The following models developed by authors of a model-base aim at performing the functions of: • A model for the establishment of the criteria weights, • A model for multiple criteria analysis and for setting the priorities, • A model for the determination of a project’s utility degree, • A model for the determination of a project’s market value.

34. Model-Base According to the user’s needs, various models may be provided by a model management system. When a certain model (i.e. search for alternatives) is used the results obtained become the initial data for some other models (i.e. a model for multiple criteria analysis and setting the priorities). The results of the latter, in turn, may be taken as the initial data for some other models (i.e. determination of utility degree of alternatives).

35. When creating the Web-based decision support systems the author based their work on the following major principles and methods: •     Method of complex analysis. The use of a complex analysis makes it possible to carry out economic, technical, qualitative, technological, environmental, managerial and other kinds of optimisation throughout the life cycle of a project. •      Method of functional analysis. The expenditures associated with project functions are usually determined by taking into account the benefits of a function and the cost of its realization. •      Principle of cost-benefit ratio optimisation. Efforts are made to get maximum benefit (economic, qualitative, environmental and social, legal, etc.) at minimum project’s life cycle expenses, i.e. to optimise the cost-benefit ratio. •     Principle of interrelation of various sciences. The problem of cost-benefit ratio may be successfully solved only when the achievements of various sciences, such as management. economics, law, engineering, technology, ethics, aesthetics and psychology, etc. are used. •       Methods of multi-variant design and multiple criteria analysis. These methods allow us to take into consideration the quantitative and qualitative factors, as well as cutting the price of the project and better satisfying the needs of all interested parties. •      Principle of close interrelation between project’s efficiency and interested parties and their aims.

36. The following Decision Support Web-Based Systems have been developed in VGTU: • Innovation, • Construction, • Facilities Management, • Real Estate • Refurbishment, • Sustainable Development, • Loans, • International Trade, • Ethics.

37. Innovation DSSMultiple criteria analysis of the government alternatives of decreasing the barriers to innovation

38. Innovation DSSMultiple criteria analysis of government policies (alternative experiments) for technological innovation

39. Construction DSSFragment of analysis of construction alternatives

40. At the present moment the developed Construction DSS allows the performance of the following functions: •   Search of construction products. A consumer may perform a search of alternatives from catalogues of different suppliers and producers. •    Finding out alternatives and making comparative tables. Consumers specify requirements and constraints and the System queries the information of specific construction products from a number of online vendors. The results of the search of a concrete construction product are often provided in one table. •   Evaluation stages of alternatives. While going through the purchasing decision process a customer must examine a large number of alternatives, each of which is surrounded by a considerable amount of information (price, discounts given, thermal insulation, sound insulation, rate of harm to human health of the products, aesthetic, weight, technical specifications, physical and moral longevity). Following on from the gathered information the priority and utility degree of alternatives is then calculated. •    Analysis of interested parties (competitors, suppliers, contractors, etc.), •   The after-purchase evaluation stage. A consumer evaluates the usefulness of the product in the after-purchase evaluation stage, etc.

41. Facilities Management DSSAnalysis of facilities management (space management) alternatives

42. Facilities Management DSS Below is a list of typical facilities management problems that were solved by users: multiple criteria analysis of space management, administrative management, technical management and management of other services alternatives; analysis of complex facilities management alternatives; analysis of interested parties (suppliers, contractors), etc.

43. Real Estate DSSAnalysis of real estate alternatives

44. Capabilities to use the Real Estate DSS in alternatives multiple criteria analysis stage are: • Real estate valuation from various aspects (i.e. determination of market value, value in use, and investment value). • Multiple criteria analysis of alternatives and selection of most efficient ones. • Valuation of factors affecting the value of real estate (for example, valuation of real estate location, real estate depreciation). • The after-purchase evaluation stage. A consumer evaluates the usefulness of the real estate in the after-purchase evaluation stage.

45. Building Refurbishment DSSAnalysis of building refurbishment alternatives

46. Developed Building Refurbishment DSS include the following models: • a model of developing the alternative variants of building enclosures, • a model for determining the initial significances of the criteria (with the use of expert methods), •   a model for the criteria significance establishment, •   a model for multivariant design of a building refurbishment, •   a model for multiple criteria analysis and setting the priorities, •   a model for determination of project utility degree, •   a model for providing recommendations.

47. Building Refurbishment DSS Based on the above models, a system can make until 100,000 building refurbishment alternative versions, performing their multiple criteria analysis, determining utility degree and selecting most beneficial variant without human interference.

48. Building Refurbishment DSSAnalysis of building refurbishment alternatives

49. International Trade DSSAnalysis of international trade alternatives

50. International trade DSS after a multiple criteria analysis of the export sectors, the following can be determined: • Priority of the sectors. One can see which the sector is most competitive in the country under consideration both statically and dynamically. • Tendencies, i.e. what the percentage of increase (or decrease) of the position (i.e. comparative advantages) of the export sectors of a country under consideration with similar sectors in other countries, during the period analysed.