In a non-linear process like conical tank system, controlling the liquid level was carried out by proportional integral derivative (PID) controller. But then it does not provide an accurate result. So in order to obtain accurate and effective response, intelligence is added into the system by using fuzzy logic controller (FLC). FLC which helps in maintaining the liquid level in a conical tank has been developed and applied to various fields. The result acquired using FLC will be more precise when compared to PID controller. But FLC cannot adapt a wide range of working environments and also there is no systematic method to design the membership functions (MFs) for inputs and outputs of a fuzzy system. So an adaptive algorithm called Kalman algorithm which employs fuzzy logic rules is used to adapt the Kalman filter to accommodate changes in the system parameters. The Kalman algorithm which employs fuzzy logic rules adjust the controller parameters automatically during the operation process of a system and controller is used to reduce the error in noisy environments. This technique is applied in a conical tank system. Simulations and results show that this method is effective for using fuzzy controller.

Implementing a low cost, power efficient and high performance routing protocol in wireless sensor networks (WSNs) is an important requirement for transmitting a packet through network. In this paper we propose, a new cost and energy aware routing protocol (CEAR) that works based on the two metrics such as cost welfare metric and route score metric.A hybrid electrical energy storage (HEES) framework which holds numerous banks of heterogeneous electrical energy storage (EES) components to be specific battery and a ultra-capacitor is used for providing energy to the network exhibit in the WSN for routing. The simulation results shows that our proposed routing protocol routes the packet efficiently by choosing the best path that also reduces the cost and routes the packet with reduced power consumption. The quantitative metrics in terms of packet delivery ratio of 0.93, average end to end delay of 110 secs, packet loss ratio of 0.75, average throughput attained of 250 bits/sec and efficiency of 98-99.9% overpowers the performance of our proposed work.

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Wireless sensor networks (WSN) has a great application value and prospect in the fields of military, agriculture, environmental monitoring, medical health, industry, intelligent transportation, building monitoring, space exploration and so on. The operation of WSN is normal under lower traffic loads. But in case of an emergency situation, like fire break out large volumes of data have to be generated and delivered to the sink. Such kind of situations results in severe channel collision and thus decreases the communication throughput in medium access control (MAC) protocols. Hence data aggregation has been put forward as an essential paradigm for eliminating the redundancy. In this paper, we propose DA (Data Aggregation) MAC, a hybrid of TDMA (Time Division Multiple Access) and CSMA (Carrier Sense Multiple Access) MAC approaches which employs center at nearest source technique. Initially the nodes make use of TDMA for its slot assignment. Each node wakes up for its corresponding slot assignment and then goes to sleep mode thus saving energy. But during any emergency situation nodes participating in it change its MAC behavior by allowing contention in TDMA slots. Instead of data transmission by the one hop neighbors of the affected node, data aggregation is implemented for the node with the minimum hop distance for reducing the overhead. This data aggregation technique is called the centre at nearest source approach. The simulation is carried out by means of NS2 (Network Simulator). Analytical and experimental results show that the proposed hybrid MAC protocol outperforms in all its aspects.

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