الفهرس 
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Abstract
Finally, the neutrosophic theory can be used to enhance the enterprise strategies to attain achievements in a competitive environment. The use of neutrosophic theory with general framework of as an intelligent service is an effective method for achieving successful enterprise. The use of neutrosophic theory in thesis overcomes the technical and environments condition limitations of misjudgment, uncertainty, and inconsistency. The estimation of IoT influential factors enhances decision judgment by the use of AHP combined with neutrosophic theory to ideally reach to ideal alternatives with respect to constraints of criterions. . The case study is applied on smart village Egypt, provides a final decision for decision maker to recommend spark with percent 45%.
The second issue of IoT enterprise success, personnel selection is a vital problem that impact on the quality of management and enterprises. The use of non-traditional methods to assist decision makers to choose the right personnel in the right position becomes an obligatory condition. So the weight of our study evolved to overcome the inconsistency and uncertainty conditions that found the in MCDM environment. The proposed study integrates neutrosophic AHP with TOPSIS methods to improve the decision committee judgments by considering environmental criteria. The case study is applied on smart village Egypt, shows the efficiency for the proposed method and provides final decision to hire applicant 4 with percent 96% to be in the right position for achieving success organization.
For sake of reusability, adaptability, and replication, the proposed methodology is applied in the UK and China. The results show that users and service providers in UK are more concerned about the well-balancing between criterions. While in China, the most important factor is the connectivity to ensure all payment and business transactions can be made efficiently and quickly KNIME is not common in the UK and China. There are local solutions developed by service providers. Due to this reason, they are classified under “others”. In London, others consist of 45%; Hadoop has 34% and Spark has 21% of percentage of usage and deployment. There is a trend that others may still go up, since there are more varieties of different solutions on offer. Alibaba is one of the biggest IT service providers in China. Therefore, the difference is there are Spark and Hadoop services offered by Alibaba or non-Alibaba. Continentally, it has 20% each for Spark and Hadoop services by Alibaba (Ali) and 20% each for Spark and Hadoop services by non-Alibaba services. The remaining 20% is for all other services not using Spark and Hadoop.