A global trend has emerged recently, indicating widespread adoption of smart environments and automation across various fields. Smart environments include diverse IoT devices, presenting challenges for conventional digital forensic investigation (DFI). The interconnected nature of smart environments signifies that volatile and non-volatile, open-source and proprietary systems are involved in transactions and data flows; therefore, digital forensics (DF) for embedded and IoT devices are intense and challenging. The challenge for DF practitioners is that DF industry solutions and capabilities have traditionally focused on conventional computer operating systems. Attributable to their complex, heterogeneous, and distributed nature, these systems are inadequate for investigating cases in the emerging IoT and smart environments. This paper aims to propose an advanced DFI framework that integrates machine learning, blockchain, and fog computing techniques into the DFI framework. The framework extends the ISO/IEC 27043 international standard. The framework is advanced and adjusted to suit smart environment forensics. The proposed framework will pave the way to allow future researchers to start covering the depth of each aspect of the framework. Moreover, a hypothetical scenario is proposed to implement and assess the readiness phase of the framework within smart buildings.