This research investigates the potential of interactive structure that applies sensor-actuator system and data analytical tools to ameliorate the environment for both human and urban pollinators. At the micro level, it functions as an autonomous machine that collects information through sensing a variety of qualities. Through monitoring environmental performance and tracking behaviours of plants and pollinators, data collected would be analyzed and processed to alter the habitats for plants and pollinators. Data is visualized to raise people’s awareness of other living beings and thus to prompt the interactions. At the macro level, situated in urban Toronto, the structures form a mini-ecosystem, connecting existing large green spaces and establishing pathways for pollinators and ameliorate the urban heat island effect. At the urban scale, the structures form a system of network that could provide data about pollinator migration pattern or swarm areas; thus it could ultimately produce a data-driven learning network. Due to the pandemic, physical testings for the research were limited.