Since the 21st century, with the acceleration of people's life rhythm and the increasing number of patients with chronic diseases, taking medicine has become a part of their daily life. This system is based on the design of the smart pill box reminder system based on the single-chip microcomputer, using STM32F103C8T6 as the core of the smart pill box reminder system, which is composed of a button module, an OLED display module, an infrared detection module, a servo module, a clock module and a Wi-Fi module. As a setting module, the user can set the reminder time and dosage of the three pill boxes according to their needs. When the set time for taking medicine is reached, the user will be rem... More >

With the rapid development of Internet technology, people's shopping methods are gradually shifting from offline to online. As an important branch of this, fresh food e-commerce has gradually become a part of people's daily lives. Traditional offline fresh food markets require a large amount of manpower and material resources for operation and maintenance, which is inefficient and has serious waste of resources. Therefore, it is particularly important to develop an efficient and convenient online fresh food shopping platform. This article introduces a 'Fresh House Grocery' fresh food e-commerce system based on the Django framework. This system aims to provide consumers with a convenient and... More >

In the era of digital transformation, enterprise web applications have become indispensable tools for business operations, necessitating the efficient and reliable management of vast amounts of data. Data persistence is critical to ensure consistency, security, and scalability, especially in complex environments involving high concurrency and sensitive information. This paper reviews the key requirements for data persistence in enterprise-level web applications, such as reliability, security, scalability, and high availability, while addressing the challenges posed by modern business needs. Various persistence solutions, including relational databases, NoSQL databases, and distributed storag... More >

With the increasing incidents of fatal road injuries, there is an urgent need for developing effective road safety management systems. The study aims to develop predictive models based on machine learning to forecast the likelihood of road collisions depending on factors like weather, road condition, time, and driver behaviour in Chicago, USA. A machine learning approach has been applied to the crash dataset to evaluate the factors affecting the prevalence of road accidents. Python programming and the Jupyter Notebook platform have been used for performing descriptive statistics, correlation and three classification algorithms (Random Forest, KNN, Decision Tree and MLP Classification). Obtai... More >