Internet of Things (IoT) has sensor nodes (SNs) in its primitive layer for collecting data from an area of interest. These SNs are powered by a battery which is a significant constraint due to its limited capacity(battery) in ad-hoc IoT networks. Since these SNs are deployed in large numbers forming a network, the network's lifetime is required to be prolonged to serve the objective of deploying the SNs. If the SNs exhaust their energy at par, then the network's lifetime can easily be extended. For achieving an almost equal energy dissipation rate of SNs, the load among the SNs should be balanced. This paper has propounded a load-balanced, efficient clustering and routing (LBECR) protocol for sustainable IoT in smart cities to muddle through this issue. Since in Adhoc IoT networks, the nodes are resource-constrained, with the escalation of input variables in the fuzzy system, the number of rules increases exponentially, leading to more energy dissipation. Therefore we have designed three Fuzzy Inference Systems with minimal inputs for cluster head (CH) selection, formation of clusters and routing of data. The cost to the CH node is considered as one of the parameters of the Fuzzy system as it has a significant impact on the stability period. A fuzzy system is designed for efficient multi-hop routing, conserving a significant amount of network energy. The proposed LBECR protocol is simulated for four different cases and compared with some recent protocols. The obtained experimental results reveal significant improvement with proficiency in balancing the network load by better average energy, delayed death rate of SNs and prolonged lifetime.