BiotaFormer: Detecting biota in microscopic activated sludge images for wastewater treatment

Recognizing biota in microscopic activated sludge images is essential for effective wastewater treatment. General object detection methods face challenges in accurately recognizing the biota with various sizes and shapes, especially under constraints of computational efficiency in industry practice. This paper presents a framework called BiotaFormer to detect biota in microscopic activated sludge images for wastewater treatment. BiotaFormer recognizes and monitors biota in microscopic images to evaluate the condition of activated sludge, which optimizes the subsequent treatment process. To evaluate BiotaFormer, we introduce the Biota-12, the first dataset specifically for biota detection. Experimental results show that BiotaFormer has significant advantages in performance, demonstrating its overall effectiveness and efficiency in industry practice