In an Internet of Things (IoT), the number of interconnected devices is huge and has been increasing drastically. Their generated data requires powerful aggregated computing resources and consumes enormous energy for processing and transmission. Having said that, most IoT devices are very limited and heterogeneous in computing capabilities, causing a big challenge for designing a commonly used interconnect that is both reliable and energy-efficient. Random Linear Network Coding (RLNC) schemes have proven its capability both theoretically and in practical deployment not only to increase throughput and reliability but also to reduce latency and energy consumption. However, it is unclear how different variations of RLNC, in particular, Fulcrum codes aimed for heterogeneous devices perform in heterogeneous IoT settings. In this paper, we conduct a measurement campaign, allowing for a fair comparison among the state of the art RLNC families, with regard to energy consumption, decoding probability, and goodput. The study provides insights and guidelines for applying RLNC schemes to data transmission in heterogeneous IoT networks.