Escherichia coli (E. coli) is a primary cause of various waterborne diseases. However, detecting E. coli faces challenges in terms of speed, cost, sensitivity, and selectivity, especially in resource-limited regions. In this study, a smartphone-assisted CuO2 and β-galactosidase (β-gal)-mediated cascade colorimetric method for E. coli detection was developed. A pH-adaptable CuO2 acting as a photo-responsive oxidase was synthesized simply and combined with β-gal released from E. coli lysed by bacteriophages, enabling an enzyme-nanozyme cascade reaction. In this reaction, β-gal catalyzes the conversion of p-aminophenyl β-D-galactopyranoside (PAPG) to p-aminophenol (PAP), which subsequently inhibits the photo-responsive oxidase activity of CuO2. The photo-responsive oxidase CuO2, with its unique mechanism to generate holes for 3,3',5,5'-Tetramethylbenzidine (TMB) oxidation, overcomes the typical pH dependency of nanozymes, maintaining the optimal activity of both CuO2 oxidase and β-gal, enhancing sensitivity in the enzyme cascades. Bacteriophages, serving as specific bacterial identifiers, selectively recognize E. coli and promote the β-gal rapid release, further enhancing the detection sensitivity. This method achieves a detection limit of 15 CFU mL-1, accurately measured E. coli concentrations as low as 102 CFU mL-1, exhibited excellent recovery rates, ranging from 95.0 % to 104.1 %, with RSD between 1.3 % and 2.8 %, distinguishes the live and dead E. coli, reducing false positive and negative. Moreover, coupled with a smartphone, the sensor provides swift and accessible colorimetric data analysis, making it ideal for resource-constrained areas. In summary, this method is specific, sensitive, rapid, and cost-effective, requiring no pretreatment and offering broad potentials for bacterial detection in resource-limited areas.