A wireless sensor network (WSN) is a staple network architecture that can be widely used to support diverse applications such as smart cities, smart homes, etc. The energy consumption and security have remained more perilous challenges in it. The blockchain is a potential solution for security provisioning in WSN. However, the classic blockchain has some problems as slow transaction processing and poor scalability. Hence, to address these issues the Directed Acyclic Graph-based Trust aware Load Balanced Routing (DAG-BTLBR) is proposed in WSN that constructs DAG for blocks. The proposed DAG-BTLBR is instigated with energy-efficient unequal cluster formation using Emperor Penguin Colony (EPC) algorithm. In this step, we mitigate the hotspot problem in WSN. An Adaptive Neuro-based Dual Fuzzy (ANDual Fuzzy) system is involved to find the secure and load-balanced route for packets transmission. ANDual Fuzzy is the combination of two fuzzy logic systems that will be in a parallel way. The DAG-based blockchain is used to store the transactions in the WSN. The lightweight authentication encryption scheme is designed for addressing data security requirements (data integrity, and confidentiality) and resource constraint issues of sensors. Initially, lightweight encryption is implemented by XTEA with Chaotic Map algorithm, whereas message authentication is implemented by Blake-256 algorithm. We computed the performance of our DAG-BTLBR model and compared it to the previous models by several evaluation criteria, which are implemented in NS3 (version 3.26). Our proposed model simulation results establish the performance and security improvements by minimizing end-to-end delay, time consumption, packet loss rate, and energy consumption, maximizing the throughput.