Every manufacturing discipline is evolving rapidly with the emergence of Industry 5.0, which is defined as the incorporation of advanced technologies to enhance sustainability, human imperative, and resilience. Logistic activities inside a manufacturing facility is not an exception for this evolution. Industrial internet of things (IIoT) as a primary enabler for the digital transformation provides the companies with great opportunities. In this context, firms need a guidance for harmonious integration of IIoT technologies into internal logistics. Existed theoretical knowledge has not addressed this issue explicitly. Therefore, the thesis is aimed at exploring the selection and integration of IIoT into internal logistics for a more smart, automated, and connected factory. The purpose of the thesis is achieved by a qualitative case study approach in a large multinational machinery manufacturing company. The study begins with a literature review constructing a theoretical framework to answer the research questions. then, semi structured interviews, document review and observations were employed as data collection methods. Three use cases: sensors for automatic replenishment, pick to light indicators for kitting and automated goods receiving are studied thoroughly for understanding the practical aspects. Thorough analysis of the collected data shows that the challenges being faced are technological, organizational, external, and human related. Also, critical factors which impact the integration of IIoT technologies and must be considered during the process are addressed through the analysis. Connecting these findings together, a roadmap has been created with a detailed explanation of actions to be taken in each step. To the existing theoretical knowledge, this thesis adds the knowledge of human and organizational factors and how to address them through developing a roadmap. Also, this knowledge will guide the companies to better prepare their workforce. Additionally, the roadmap helps the practitioners in strategic decision making and to develop further understanding for practical implementation. Offering insights into the challenges and critical factors this work can guide future research and development in smart logistics systems.