Increasing greenhouse gases impose severe concern over the environment resulting in rising dangerous calamities of climate change in the form of floods, etc. Major disadvantages like intermittency of electric vehicles need to be charged after traveling fixed distance. The paper develops an algorithm for a selected industrial electric vehicle to be controlled at different speeds that envisages working on real time IoT (Internet of Things) based GPS (Global Positioning System) signals. It engages the ARM core based STM micro-controller in conjunction with mesh networked BLE (Bluetooth Low Energy) to govern the operations besides enabling it to be dynamically monitored. The system design considers the vehicle parameters that include the speed of vehicle and the engine, SoC (State of Charge) and SoH (State of Health) of battery together with real time GPS based navigation system using IoT bundled GPS based maps interface. The methodology involves a closed loop monitoring with specified sequence of steps that augur the system to operate at defined speed over designated work shifts and schedules. The procedure introduces an embedded C environment with a process of unit-testing based simulation to capture the merits of schema in terms of an improved vehicle performance under varying parametric conditions.