Internet of Things (IoT) forensics faces challenges such as acquiring, identifying, and analyzing evidence. This process is complex due to the exponential growth in IoT devices and the security requirements such as anonymity, non-tampering, and tracking necessary in this context. The blockchain paradigm has been widely used to solve these challenges in IoT environments. However, collecting a large volume of data in IoT can typically lead to bottlenecks in the blockchain. This paper proposes a system called IoTP4Chain, which can collect, identify, aggregate, and filter data from IoT systems based on a taxonomy and respective library of preprocessing functions that execute on a programmable data plane. This allows for efficient and scalable forensic evidence collection on IoT systems before storing that data on a blockchain.