# IoT-Driven Intelligent Scheduling Solution for Industrial Sewing Based on Real-RCPSP Model
## 2 Related Works
### Implementation Challenges and Future Directions  
Several studies have focused on the challenges and directions in implementing IIoT and Industry 4.0 applications. [PERSON] et al. [37] presented barriers to adopting Industry 4.0 technologies in the manufacturing sector and pointed out challenges in data management. [PERSON] et al. [38] studied and analyzed the barriers to the implementation of Industry 4.0 in the textile industry, including lack of trained personnel, lack of understanding and commitment from business management, lack of government support and policies, lack of good investment in research and development; high implementation costs; fear of failure; and integration and compatibility issues. After analyzing and identifying the barriers, the author proposes a triple helix-based framework for collaborative activities among stakeholders, including garment industry actors, training units, and state management units, to help formulate policies and develop strategies for effectively implementing Industry 4.0 in the Indian textile industry. [PERSON] and [PERSON] [39] studied the implementation of IIoT in the renewable energy sector, highlighting the potential benefits and obstacles in integrating IIoT technologies into current renewable energy systems. [PERSON] et al. [40] studied and reviewed the critical success factors for adopting Industry 4.0 technologies in environmentally sustainable manufacturing. In their study, the authors emphasized the role of leadership and corporate culture in influencing the successful implementation of new technologies into enterprises' manufacturing operations. [PERSON] et al. [41] comprehensively researched, analyzed, and evaluated Industry 4.0, giving specific assessments of the work and application deployment status in the past, present, and future. [PERSON] et al. [42] studied the implementation of innovative factory models, learning about the leading technologies and strategies to achieve production goals in the current period. Extensive research on IIoT and Industry 4.0 has shown significant progress and applications in various industrial sectors. Recent studies highlight the transformational potential of IoT technologies in revolutionizing manufacturing processes, enhancing predictive maintenance strategies, and boosting overall operational efficiency. However, challenges such as security threats, implementation complexity, and the need for robust data analytics frameworks remain. Future research should address these challenges and explore integrating emerging technologies such as artificial intelligence, blockchain, and 5G to enhance IoT systems' capabilities further. As shown in the papers above, implementing IIoT improves efficiency in many manufacturing industries. However, there have been no specific studies on the application of IoT in the industrial garment industry to monitor and manage production, thereby supporting the effective planning of industrial garment orders. The study focuses on the application of IoT in the industrial garment industry, based on the data collected from the IoT sensor system, which will be integrated with the MIS system of the industrial garment enterprise to support real-time monitoring and management. In addition, the combination of the Real-RCPSP production planning problem will help industrial garment enterprises automate production planning and management more effectively. The research highlighted earlier indicates that IIoT implementation provides substantial advantages to the production processes of enterprises. However, there has been no specific research on the application of IoT in the garment manufacturing industry, a sector that contributes significantly to the GDP of many countries worldwide, including Vietnam (currently, Vietnam has about 7000 garment enterprises, employing approximately 3 million workers (VnEconomy, VnEconomy.vn 2023), and achieving an export value of USD 44 billion in 2024 (VnEconomy, VnEconomy.vn 2024)).