Selecting Key Smart Building Technologies for UAE Prisons by Integrating Analytical Hierarchy Process (AHP) and Fuzzy-TOPSIS

Procedure of MCDM Process for the Selection of Smart Building Technologies
Step 1. Identification of Smart Building Technologies
Smart building technologies to be used in UAE prisons were identified by semi-structured interviews and questionnaire survey conducted in the prior stage of this study. The interview was accomplished by the participation of fourteen interviewees from the top management working in the UAE prison and construction sectors. Subsequently, 238 participants, including people with good knowledge and experience of prisons and construction, completed a questionnaire survey. As a result, nine smart building technologies were
selected for the pilot survey involving AHP and Fuzzy-TOPSIS. These smart technologies include the lighting system, fire protection system, safety and security system, HVAC, vertical transportation system, information and communication network system, electrical system, building automation system, and hydraulic and drainage system.
Step 2. Identification of Criteria and Sub-Criteria for Smart Building Technologies
The next step of the decision-making process is identifying the criteria and subcriteria for smart building technologies. This was accomplished based on the literature review, interviews, and survey. By collating evidence from these broad sources, a questionnaire was developed, comprising pairwise comparisons of main criteria, subcriteria and smart building technologies using Expert Choice online software and provided
to 14 experts from the top management level working in the construction and prison sector of the UAE. The demographic information of experts revealed that 11 out of 14 were male; half had master’s degrees, whereas five experts had bachelor’s degrees. The 11 experts had more than ten years of experience serving in higher positions in the government and private sectors. The experts were briefed about the study’s objectives and asked to compare the weights of each criterion and sub-criteria on a 9-point Saaty scale.

Step 3. Deriving the Fuzzy Weights of Criteria Using the AHP
The AHP was employed to derive the weights of all pairwise comparisons from the questionnaire survey, resulting in local and global weights for each criterion and subcriteria. The pairwise comparison result of experts (k) on the relative weight of criteria i over sub-criteria j is given by ij(k).

Step 4. Aggregating the Fuzzy Weights from All Decision-Makers
The weights of different criteria obtained from the AHP process were aggregated to incorporate multiple decision-makers. This involved pooling the decision makers’ opinions on the relative weights of different criteria to get the aggregated fuzzy rating for each alternative.

Step 5. Assessing the suitability of smart technology applications in prisons using the Fuzzy TOPSIS

The fuzzy TOPSIS method was used to assess the suitability of different smart building technologies for applications in different prison scenarios.

A closeness coefficient was used to rank the order of alternatives:

智能建筑技术在阿联酋监狱中的选择的多准则决策过程
步骤 1. 智能建筑技术的识别
在本研究的初期阶段，通过半结构化访谈和问卷调查识别了将用于阿联酋监狱的智能建筑技术。访谈由来自阿联酋监狱和建筑行业顶级管理层的十四位受访者参与完成。随后，包括对监狱和建筑有丰富知识和经验的238名参与者完成了问卷调查。据此，选定了九种智能建筑技术进行试点调查，涉及层次分析法（AHP）和模糊TOPSIS方法。这些智能技术包括照明系统、消防保护系统、安全与监控系统、供暖、通风与空调系统、垂直交通系统、信息和通信网络系统、电气系统、建筑自动化系统以及液压和排水系统。
步骤 2. 智能建筑技术评价指标和子指标的识别
决策过程的下一步是识别智能建筑技术的评价指标和子指标。这基于文献综述、访谈和调查完成。通过综合这些广泛来源的证据，开发了一份问卷，其中包含主要指标、子指标与智能建筑技术之间的成对比较，使用专家选择在线软件并提供给14位来自阿联酋建筑和监狱行业顶级管理层的专家。专家的人口统计学信息显示，14位专家中有11位是男性；其中一半拥有硕士学位，而五位专家拥有学士学位。这11位专家在政府和私营部门的高层职位上拥有超过十年的经验。专家们被简要介绍了研究的目标，并被要求在9点萨蒂量表上比较每个指标和子指标的权重。
步骤 3. 使用层次分析法推导评价指标的模糊权重
层次分析法被用于从问卷调查中推导所有成对比较的权重，从而得到每个指标和子指标的局部和全局权重。专家（k）对指标i相对于子指标j的相对权重的成对比较结果由ij(k)给出。
步骤 4. 从所有决策者中汇总模糊权重
从层次分析法过程中获得的不同准则的权重被汇总，以纳入多个决策者。这涉及汇总决策者对不同准则相对权重的意见，以获得每个备选方案的汇总模糊评分。
步骤 5. 使用模糊TOPSIS评估智能技术在监狱中的应用适宜性
使用模糊TOPSIS方法评估不同智能建筑技术在不同监狱场景中的应用适宜性。
使用接近系数对备选方案的顺序进行排序：