The emergence of new era of Internet of Things or IoT have encouraged intensive if not extensive usage of modern mobile apps, thus multi-ISA equipped multicore processor gain great potential to be used for more efficient instruction binary processing in near future. In order to support this ISA diversity of computing platforms, mix modes of statically and dynamically Binary Translation and Optimization system, popularly consists of QEMU and LLVM or similar system, is the default technique used. However this complex system exhibits heavy slowdown (60x slowdown as compare to generic QEMU) 21 which impede its performance especially for short running application codes, typically used in IoT based apps applications. This research introduce a dual binary code translation engines to support apps based and kernel based application codes, through utilising multithreaded supported apart of original single thread supported binary translation processing in run-time. The dual engine consists of TCG generator from QEMU, and LLVM which include rich optimisations library. The evaluation through PARSEC-3.0 Benchmark shows our Hybrid DBTO system achieved performance improvement approaching 2.0x for apps based programs and 1.25x for kernel based programs, for x86 to X86-64 emulation. This technique possess great potential and serve as research based platform for future binary translation technique development, including adaptive method. © 2016 IEEE.