Abstract Secure and robust Industrial Internet of Things (IIoT) statistics dealing with cloud infrastructures are vital as commercial gadgets become more networked. IIoT systems accommodated in the cloud should shield personal statistics, ensure uninterrupted operations, use information insights to make decisions and reduce electricity consumption. Several industries have been transformed through IIoT programs, which depend closely on cloud infrastructure for statistics processing and garages. Energy performance and the safety of sensitive business statistics are predominant issues. Some problems that need addressing are secure data transmission, invasion of privacy, and data breaches. It is not a simple task to optimise power efficiency without compromising actual-time records processing. The Optimised Dynamic Clustering and Energy-Efficient System (ODC-EES) is a unique approach for cloud-based IIoT information control and employers that uses stepped-forward adaptive clustering strategies. Strengthening facts security whilst streamlining strength use, the recommended method blends present-day encryption protocols, access controls, and power-aware helpful resource allocation. This method promotes sustainable electricity practices even by ensuring adaptability to the ever-converting IIoT information. Manufacturing, strength, logistics, and healthcare are a few commercial sectors that might benefit from the proposed method. The counselled approach seeks to enhance the dependability and performance of manufacturing strategies by making information more stable and using less strength. To demonstrate the system's efficacy in enhancing statistics protection, optimising energy usage, and ensuring the fresh operation of IIoT programs in cloud environments, these simulations will evaluate its overall performance in numerous situations.