Choosing a university specialization is a challenging decision for high-school students. Due to the lack of guidance and limited online resources, students base their decisions on subjective perceptions of family and friends. This increases the risk of high university dropout rates, and students changing their university disciplines. To address the aforementioned drawbacks, this research paper presents a Personalized Career-path Recommender System (PCRS) to provide guidance and help high school students choose engineering discipline. The design of PCRS is based on fuzzy intelligence of N-layered architecture and uses students’ academic performance, personality type, and extra-curricular skills. The association between personality type and engineering discipline was built using a sample of 1250 engineering students enrolled in seven engineering disciplines at An-Najah National University. PCRS is implemented as a mobile application and it is tested against an evaluation sample of 177 engineers. The sample consists of graduate or undergraduate engineers who are satisfied with their engineering disciplines. The evaluation examined the agreement between the recommendations generated by PCRS and the 177 actual engineering discipline of the sample. The evaluation results proved a slight agreement between the suggested recommendations of PCRS and the actual discipline of the research sample. Hence, PCRS is capable of providing guidance to high-school students who are interested in pursuing their studies in Engineering. The PCRS application is the first career-path recommender to target Palestinian community and other developing countries in the MENA region. The design of PCRS is scalable and it can be expanded in the future to consider other academic majors of higher education.

Water is the most important resource for life, such that it plays a vital role in our everyday activities. And due to the shortage of water resources, there is an increasing importance of a fair water distribution system among citizens that cope with different activity variations among citizens also it can control water consumption. Moreover, due to the growth of technology and the existence of the internet of things (IoT) and big data analytics in the cloud, there is an increasing need for a system that monitors the citizen consumption and controls the distribution according to an adaptive knowledge base. Therefore, this paper presents a water distribution management system that is smart and adaptive to citizen demands, and it is also able to control the consumption by providing the optimum amount of water in order to conserve water and sustain the citizen activities as well. The design of the system merges the existing IoT infrastructure, big data analytics for collecting and analyzing user demands and cloud computing for storing the data for further processing