Distributed IoT based sensor analytics for power line diagnosis

A distributed power line diagnosis systenciin which at least one power line issue is determined based on one or more computations comprising;

• a) a firmware to receive a plurality of electrical line data over a communications network;
• b) a real time data processing system associated with distributed databases;
• c) a local firmware board;
• d) a data hub;
• e) an IoT server;
• f) a multi-classification machine learning engine associated with the IoT server;
• g) a display module associated with one or more processors and user interface;
• wherein a power line issue is mapped onto a depiction on a user interfaces;
• and wherein the power line issue is determined based on a computation through at least one of the local firmware board, the data hub, and the IoT server;
• and
• h) an alarm module to raise an alarm when a pre-set condition is breached;
• wherein the alarm module is associated with the multi-classification machine learning engine.

A method of diagnosing distributed power line issues comprising:

• a) receiving at least one electrical reading at a firmware board computation engine;
• b) transmitting an output of firmware board computation engine to a data hub computation engine over a communication network;
• c) transmitting an output of the data hub computation engine to a big data server, wherein a machine learning engine is associated with at least one of the big data server and a computer database hosting historical data;
• d) determining at least one electrical line issue based on one or more computations on the big data server using the historical data;
• e) visualizing at least one electrical line issue based on an analysis through the big data server;
• f) indicating at least one electrical line issue through a user interface dynamic;
• and
• g) setting, through a processor, an alarm for at least one electrical line issue through at least one of a rule based engine and a multi-classification machine learning engine;
• wherein the alarm is set through at least one of a rule based engine and multi-classification machine learning engine;
• wherein the user interface dynamic is a predicative maintenance circular gauge;
• wherein the communications network is one of WiFi, 2G, 3G, 4G, GPRS, EDGE, Bluetooth, ZigBee, Piconet of BLE, Zwave or a combination thereof;
• wherein the alarm is raised over the communication network through one of a notification on the mobile application, Short Message Service (SMS), email or a combination thereof.