Park Vale Academy

Understanding the built environment is essential to the overall study of population dynamics, grid infrastructure, emergency response, among others. In the United States there are multiple classifications for buildings within the built environment such as residential, signifying family homes while commercial buildings consist of apartments or larger structures which are multi-purpose. While there is a high level of understanding of where these aforementioned structures are located, there is a third class of structures, mobile home parks (MHP) which have been under-represented in the literature despite there being an estimated 2.7 million of them within the United States. Research has shown that individuals who reside in MHP are at higher risk to extreme events due to their location and structural integrity of residence. Attention must now turn to identifying MHP at scale to help first responders and policy makers understand where these at risk populations reside. To address for this gap, we develop a novel methodology to infer MHP at scale based off morphologies derived at a building level. We show that across 3 million buildings in 6 states within the United States it is possible to identify MHP with 83% accuracy. This novel approach to identify MHP from other structures within the built environment using a machine learning approach provides a new tool to leverage in relation to helping at-risk populations.

This all-inclusive research paper plunges into the transformative nature of artificial intelligence (AI) in healthcare, emphasizing its ability to change patient care and administrative activities. The investigation examines systematically how AI technologies are creating major improvements towards patients’ outcomes and enhanced operational efficiency within the healthcare systems. From diagnostics to personalized treatment plans and administrative tasks, AI is being integrated using sophisticated algorithms in numerous aspects of healthcare delivery. One major focus is improving diagnostic accuracy. AI-backed diagnostic tools such as image recognition software as well as predictive models have outperformed traditional methods in medical condition identification and diagnosis. For instance, artificial intelligence algorithms show exceptional skills in analysing medical images resulting to earlier detection as well as accurate diagnoses of diseases like cancer, cardiovascular conditions among others neurological disorders. These enhancements not only allow for timely intervention but they significantly reduce instances where diagnosis goes wrong hence enhancing patient prognosis while reducing health costs drastically. The ability to customize personalized therapy is yet another essential aspect of AI in healthcare. With such information as genetic data, medical records and lifestyle factors, and other patient information, AI systems can develop individualized treatment plans. It is for this reason that personalization of treatments enhances their efficiency while reducing the risk of any adverse effects as well as ensuring patients’ adherence to prescribed therapies. Besides, it is important to note that AI-driven predictive models are helpful in identifying individuals with a higher probability of developing specific conditions thereby allowing interventions aimed at preventing diseases and bettering overall population health. AI has also transformed administrative tasks within hospitals besides its clinical applications. For example, AI driven automation is now used to streamline scheduling of appointments or billing processes or even storage of patient records which are normally considered routine administrative works. In addition, through these means there is reduced burden on administrative duties for healthcare workers who continue to perform them with increased precision and timeliness. The net effect is that time and resources can be redirected towards more direct patient care thus improving service quality across the board’s entire system

Smart cities are one of the most important inputs to the current strategic plans of any country, especially after the emergence of the concept of sustainable development and the huge boom in construction, information and communications technology and the world's orientation towards the concept of digitization. The smart city is an integration of technology-based cities such as digital cities, knowledge-based cities and green cities. These cities are based on several dimensions, including smart mobility, which is a dangerous indicator in measuring the extent of cities' intelligence, as traditional mobility is one of the most important problems of cities and may be a source of noise, visual and environmental pollution. Accordingly, experts and researchers are interested in linking technological development to solving mobility problems, and questions arise about the effectiveness of smart mobility in achieving sustainable smart city planning. Accordingly, the study seeks to reach the most important policies supporting the achievement of smart transportation, by monitoring the concept of smart mobility, its most important components and pillars, smart transportation systems, their applications and components that rely heavily on information and communications technology. The research also addresses the collection and analysis of the most important policies adopted to support smart transportation procedures, as well as systems for collecting and storing data and converting it into information and smart systems. تعد المدن الذكية من اهم مدخلات الخطط الاستراتيجية الحالية لاي دولة وبالاخص بعد ظهور مفهوم التنمية المستدامة والطفرة الهائلة في تكنولوجيا البناء والمعلومات والاتصالات وتوجه العالم لمفهوم الرقمنة، وتعد المدينة الذكية اندماج بين المدن المعتمدة على التقنيات مثل المدينة الرقمية والمدن التى تعتمد على المعرفة والمدن الخضراء ،كما ترتكز هذه المدن على عدة ابعاد منها التنقل الذكي الذي يعتبر مؤشر خطير في قياس مدى ذكاء المدن، حيث ان التنقل التقليدي يعد من اهم مشاكل المدن فقد يكون مصدر للتلوث السمعي والبصري والبيئي وعليه يهنم الخبراء والباحثين بربط التطور التكنولوجي بحل مشكلات التنقل وتظهر التساولات حول مدى فاعلية التنقل الذكي في الوصول الى تخطيط المدن الذكية المستدامة. وعليه تسعى الدراسة للوصول الى اهم السياسات الداعمة لتحقيق النقل الذكي، وذلك من خلال رصد مفهوم التنقل الذكى واهم مكوناته وركائزه و انظمة النقل الذكى وتطبيقاتها ومكوناتها التى تعتمد بشكل كبير على تكنولوجيا المعلومات والاتصالات، كما يتطرق البحث الى جمع وتحليل اهم السياسات المتخدة لدعم اجراءات التنقل الذكى وكذلك نظم جمع وتخزين البيانات وتحويلها الى معلومات وانظمة ذكية