Companies take project-based management as their organizational strategy, and project quality assurance plays a vital role in improving customer satisfaction and enhancing corporate image. Starting from the perspective of optimizing project quality, this paper assigns different quality influencing factors to each project and each task of the project, divides the labor resources shared by multiple projects in the enterprise according to the skill level, and transforms the problem of project quality optimization. The problem of the highest skill level of labor resources allocated to all projects of the enterprise is designed, and algorithms are designed to achieve the optimization of project quality through the optimal allocation of labor resources. The various links in this article are closely related to form a comprehensive, scientific, and systematic research system for optimal human resource allocation, human resource management, and development. Finally, case analysis is used to confirm the usability of the model and provide a quantitative method and perspective for project-oriented companies to allocate workforce.

With the development of sensor technology and the Internet of Things (IoT) technology, the trend of miniaturization of sensors has prompted the inclusion of more sensors in IoT, and the perceptual feedback mechanism among these sensors has become particularly important, thus promoting the development of multiple sensor data fusion technologies. This paper deeply analyzes and summarizes the characteristics of sensory data and the new problems faced by the processing of sensory data under the new trend of IoT, deeply studies the acquisition, storage, and query of sensory data from the sensors of IoT in e-commerce, and proposes a ubiquitous storage method for massive sensory data by combining the sensory feedback mechanism of sensors, which makes full use of the storage resources of IoT storage network elements and maximally meets the massive. In this paper, we propose a ubiquitous storage method for massive sensing data, which makes full use of the storage resources of IoT storage network elements to maximize the storage requirements of massive sensing data and achieve load-balanced data storage. In this paper, starting from the overall development of IoT in recent years, the weak link of intelligent information processing is reinforced based on the sensory feedback mechanism of sensor technology.

This paper conducts an in-depth analysis and research on the optimization of the labor resource management information platform through the Internet of Things (IoT) technology; through the collection, classification, and data search functions of this application system, it meets the supply and demand of professional talents within a certain enterprise. At the same time, it also realizes the curriculum training application on improving the skills and literacy of the employees of a certain enterprise, and it can learn the enterprise curriculum training from the comments of the employees on the enterprise curriculum. The effect of the enterprise course training can be learned from the comments of the employees on the enterprise course, providing an important reference basis for the future revision of the enterprise course training content. The performance of the participants in the training also has objective data for reference, so that the situation will not be disconnected from reality, and the interaction between enterprise management and employees can achieve a balanced effect. The goal of this workforce resource management system is to create a systematic workforce resource management platform for professional talents and help enterprises achieve the goal of speeding up and increasing efficiency. The system interface provided by the third party is used for horizontal data expansion to realize the sharing of basic information or video data as well as system expansion to realize real-time monitoring and management of project works. The cloud platform realizes efficient management and scientific application of construction site projects by construction management departments, which better solves the current problem of lack of supervision at construction sites.