The high expense of upgrading traditional analog and digital smart grid meters with network sensor devices is a major implementation cost for collecting energy consumption statistics. A cost-effective solution for the information extraction from the meter images is to use a systematic IoT-Based periodic digital imaging methodology instead of manual reading techniques. The computations on and secrecy of the extracted energy information are enabled by the additive homomorphic nature of encryption in Paillier's cryptosystem. The encrypted data is then, retrieved via the IoT device with the image sensor installed at the industrial, commercial and residential subscriber metres. This power consumption ciphertext is subjected to decentralized progressive aggregation as it is en route online from the end user grid meter at level 0 to the level $n$ semi-trusted final collector for decryption through numerous minimum height spanning trees (MHST) constructed at $n-1$ geographic levels. The proposed scheme's robustness to replay, false data injection (FDI) attacks and data integrity are ensured by pairing based Boneh-Lynn-Shacham (BLS) short signature, time stamping and SHA-256 function. This practical technique, therefore, facilitates secure and distributed data aggregation from various sorts of users in a hierarchical fashion in an efficient manner.