Understanding and monitoring natural ecosystems is necessary for an efficient implementation of sustainable strategies to tackle climate and environmental-related challenges to protect and improve the quality of air, water, and soil. Within the I-Seed project, a robotic ecosystem is envisioned to be used for collecting environmental data in-situ with high spatial and temporal resolution across large remote areas where no monitoring data are available, and thus for extending current environmental sensor frameworks and data analysis systems. As part of this, the laser-induced fluorescence (ALF) imaging system has been integrated with the drone-based platform and flight path generator to a complete mobile robotic system. A release system for I-Seeds attached to the drone was designed and constructed. All these activities have been integrated and resulted in a drone-based swarm hardware system which combines the three main phases for the I-Seeds-Drone scenario: spreading, localization and read out of the I-Seeds. In this paper, the integrated hardware and software components are presented, described and illustrated in more detail. For this I-Seed model all steps have been developed and some initial results will be presented.