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The Wireless Sensor Network technologies has great advantage that provide us with cheap solution to deal with telecommunication infrastructure problem that don’t exist in extreme and isolated area. However, the biggest problem exist within wireless sensor network was WSN node limited power. In this paper we try to provide battery less power sources for Wireless Sensor Network Node using Redox method. Using 9 combinations of electrodes circuits, it can provide 6.53 volt and turn on Arduino Mini Pro microcontroller. However, the second it turns on Arduino Mini Pro the voltage drops to 1.73 Volts. Hence this energy harvester can provide power to the Arduino Mini Pro microcontroller with unstable power supply.

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one of the advantages of Wireless Sensor Network would be its ability to reduce cost of communication system using node to node communication. Because of many things data transfer is Wireless Sensor Network operation sometimes has disturbance. A routing algorithm is a network coding that intends to enhance network performance for better operation with or without any disturbance. Fuzzy TOPSIS and SAW as MCDM algorithm is proposed for routing algorithm in Wireless Sensor Network operation. From our simulation both SAW  and Fuzzy Topsis algorithm can be used in network coding (routing) to provide better QOS for Wireless Sensor Network compare with shortest path routing. For delay it perform better at about 2/3 (shortest path routing 50 millisecond, both SAW and Fuzzy Topsis algorithm 33 millisecond), and for packet loss at about 3/4 (shortest path routing 21 bit loss, both SAW and Fuzzy Topsis algorithm 16 bit loss). From our simulation both SAW and Fuzzy Topsis algorithm algorithm has benefit which is lower delay and packet loss but at higher cost which is more hopping for communication channel (shortest path routing 3 hopping, both SAW and Fuzzy Topsis algorithm 5 hopping)

One of the advantages of Wireless Sensor Network would be its ability to reduce cost of communication system using node to node communication. However Wireless Sensor Network also had a disadvantage which is has limited energy which is include this as low power application. This small energy capacity has limit WSN node capability to operate for a long time. In this paper, we compare power consumption for 3 popular microcontroller development platforms that use for fast development and prototyping Wireless Sensor Network node. The power consumption was including active mode (using most energy) and deep sleep mode (using least energy) operation. From benchmarking we can see that lolin ESP32 as a microcontroller development platform has the most efficient in power consumption which is only 40 mA in active and 0.05 in deep sleep mode, compare with arduino pro mini 8 mA in active and 0.3 mA in deep sleep mode, and wemos D1 mini 74 mA in active and 0.13 mA in deep sleep mode. This low power consumption in deep sleep mode has resulting in longer operational time which is almost 48 Month for lolin ESP32