Internet of Things (IoT) are increasingly being adopted into practical applications such as security systems, smart infrastructure, traffic management, weather systems, among others. While the scale of these applications is enormous, device capabilities, particularly in terms of battery life and energy efficiency are limited. Despite research being done to ameliorate these shortcomings, wireless IoT networks still cannot guarantee satisfactory network lifetimes and prolonged sensing coverage. Moreover, proposed schemes in literature are convoluted and cannot be easily implemented in real-world scenarios. This necessitates the development of a simple yet energy efficient routing scheme for wireless IoT sensor networks. This paper models the energy constraint problem of devices in IoT applications as an optimization problem. To conserve the energy of device nodes, the routing protocol first aggregates devices into clusters based on a number of different features such as distance from base station, data/message length and data sensed from the environment in the current epoch. Then, a cluster head is elected for each cluster and a directed acyclic graph (DAG) is generated with all the cluster heads as nodes. Edges represent communication intent from transmitter to receiver and the edge weights are computed using a formulated equation. The minimum cost path to the base station is computed to allow for efficient real-time routing. Sleep scheduling is also optionally used to further boost network energy efficiency. The proposed routing protocol has been simulated and outperforms existing routing protocols in terms of metrics such as number of active nodes, energy dynamics and network coverage.