The　idea　of　big　data　has　gained　extensive　attention　from　governments　and　academia　all　over　the　world.　It　is　especially　relevant　for　the　establishment　of　a　smart　city　environment　combining　complex　heterogeneous　data　with　data　analytics　and　artificial　intelligence　(AI)　technology.　Big　data　is　generated　from　many　facilities　and　sensor　networks　in　smart　cities　and　often　streamed　and　stored　in　the　cloud　storage　platform.　Ensuring　the　integrity　and　subsequent　auditability　of　such　big　data　is　essential　for　the　performance　of　AI-driven　data　analysis.　Recent　years　has　witnessed　the　emergence　of　many　big　data　auditing　schemes　that　are　often　characterized　by　third　party　auditors　(TPAs).　However,　the　TPA　is　a　centralized　entity,　which　is　vulnerable　to　many　security　threats　from　both　inside　and　outside　the　cloud.　To　avoid　this　centralized　dependency,　we　propose　a　decentralized　big　data　auditing　scheme　for　smart　city　environments　featuring　blockchain　capabilities　supporting　improved　reliability　and　stability　without　the　need　for　a　centralized　TPA　in　auditing　schemes.　To　support　this,　we　have　designed　an　optimized　blockchain　instantiation　and　conducted　a　comprehensive　comparison　between　the　existing　schemes　and　the　proposed　scheme　through　both　theoretical　analysis　and　experimental　evaluation.　The　comparison　shows　that　lower　communication　and　computation　costs　are　incurred　with　our　scheme　than　with　existing　schemes.