The rise of the Internet of Things (IoT) has created a problem of abundance in digital forensics, presenting unique challenges that require novel solutions – including more advanced and scalable tools and techniques. In this paper, we introduce Digital Forensics 4.0 Framework which is a complete data acquisition, analysis and preservation mechanism from various levels to overcome the challenges mentioned above. The platform also bundles in tools to pull forensic data from IoT, analyse network traffic and collect cloud-based evidence providing a comprehensive picture of incidents with an IoT component. The platform leverages machine learning algorithms to automate detection of anomalies, makes investigations much faster and more accurate with a sophisticated framework. This methodology was demonstrated by the development and model’s framework through prototype implementation and case situations in real world to show feasibility of effectively using this approach for monitoring and actionable analytics for malicious events, illegal transmission of data, or security breaches. According to the results, the framework managed to record and analyse traces gathered from an IoT device pool including valuable insights for forensic investigators. But issues of large IoT network s callability and legal access to cloud data still need to be resolved. The project’s future work will focus on scalability, privacy-preserving properties and AI-driven techniques beyond what is already included in the framework. In conclusion, the proposed Digital Forensics 4.0 Framework seems a good alternative scenario for IoT forensics as an illustrative lead to more efficient and powerful digital investigations in this developing IoT environment.