Wireless Sensor Network (WSN) is deployed to monitor physical conditions in various places such as geographical regions, agriculture lands, office buildings, industrial plants and battlefields. WSNs are prone to different types of failures due to various environmental hazards like interference and internal failures (such as battery failure, processor failure, transceiver failure, etc). In such a situation, the sensed data cannot be transmitted correctly to the data center and the very purpose of deploying WSNs is not effective. Since it is difficult to monitor the network continuously through a manual operator, the nodes in WSN need to be capable of overcoming the failures and transmit the sensed data in proper order to the data center. Sensor network should be designed such that it should be able to identify the faulty nodes, try to rectify the fault and be able to transmit the sensed data to data center under faulty condition of a network and thereby make the network fault-free and thus enhance the fault tolerant capability. In this paper, we propose a novel idea of an Active node based Fault Tolerance using Battery power and Interference model (AFTBI) in WSN to identify the faulty nodes using battery power model and interference model. Fault tolerance against low battery power is designed through hand-off mechanism where in the faulty node selects the neighboring node having highest power and transfers all the services that are to be performed by the faulty node to the selected neighboring node. Fault tolerance against interference is provided by dynamic power level adjustment mechanism by allocating the time slot to all the neighboring nodes. If a particular node wishes to transmit the sensed data, it enters active status and transmits the packet with maximum power; otherwise it enters into sleep status having minimum power that is sufficient to receive hello messages and to maintain the connectivity. The performance evaluation is tested through simulation for packet delivery ratio, control overhead, memory overhead and fault recovery delay. We compared our results with Fault Detection in Wireless Sensor Networks (FDWSNs) for various performance measures and found that AFTBI outperforms compared to the results of FDWSN.