IEEE SENSORS JOURNAL, VOL. 15, NO. 7, JULY 2015

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A Self-Powering Wireless Environment Monitoring System Using Soil Energy Fu-To Lin, Student Member, IEEE, Yu-Chun Kuo, Jen-Chien Hsieh, Hsi-Yuan Tsai, Yu-Te Liao, Member, IEEE, and Huang-Chen Lee, Senior Member, IEEE

Abstract— This paper presents a self-powering wireless environment monitoring system using renewable and cost-efficient soil energy. The D-size (55.8 cm3 ) soil energy cell with carbon and zinc electrodes can produce ∼60–100 µW, depending on the water contents and microbial reactions in the soil. The RC circuit model of a soil cell is proposed for understanding the electrical characteristics of the cell. The wireless sensing system, including temperature and air moisture sensors, a custom low-power capacitive sensor readout silicon chip, a microcontroller, and a Bluetooth low-energy transmitter, is demonstrated for long-term environmental monitoring solely by the fabricated D-size soil cell. The capacitive sensor readout chip is fabricated in a 0.18-µm CMOS process and only consumes 3 µW. The capacitance readout range is 160–200 pF. The total power consumption of the wireless temperature and air moisture monitoring system is ∼20 µW and 1 mW in the sleep mode and the active wireless data communication operations, respectively. The new technology can enable remote field environment monitoring with less labor-intensive work and battery replacement. Index Terms— Soil energy, renewable energy, wireless sensor, temperature sensor, humidity sensor, integrated circuit.

I. I NTRODUCTION

R

ECENTLY, due to increasing population, severe weather changes, and global warming, food and energy crises have become critical issues around the world. Environment monitoring using advanced sensor, computing, and communication technologies has been widely utilized for precision agriculture, disaster alarm, and land protection. The emerging technology of wireless sensor networks (WSNs) provides realtime controls and communication with the physical world

Manuscript received December 2, 2014; revised January 18, 2015; accepted January 18, 2015. Date of publication February 3, 2015; date of current version May 13, 2015. This work was supported by the Ministry of Science and Technology, Taiwan, under Grant MOST103-2218-E-009-023 and Grant 102-2221-E-009-193-MY3. The chip fabrication was supported by the National Chip and Implementation Center, Taiwan. The associate editor coordinating the review of this paper and approving it for publication was Prof. Subhas C. Mukhopadhyay. F.-T. Lin and Y.-T. Liao are with the Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan (e-mail: [email protected]; [email protected]). Y.-C. Kuo, J.-C. Hsieh, and H.-Y. Tsai are with the Department of Electrical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan (e-mail: [email protected]; [email protected]; [email protected]). H.-C. Lee is with the Department of Communications Engineering, Advanced Institute for Manufacturing with High-Tech Innovations, National Chung Cheng University, Chiayi 62102, Taiwan (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JSEN.2015.2398845

to reduce the risk of food shortages and casualties from disasters [1]. To be widely deployed, wireless sensor nodes require miniaturized and self-sustaining sensory devices with advanced communication technology. A key challenge of ubiquitous sensor networks is finding a reliable energy source for their long-term operations. Wiring a power-source to sensors not only costs a vast amount of labor and resources but also leads to potential contamination produced by the batteries. Renewable and environment-friendly energy sources, such as solar, tidal, and wind power, have attracted much attention as the cost and environmental impact of fossil energy increases. However, the cost of building infrastructure for harvesting natural energy is one of the major hurdles in the ubiquitous use of these energy sources. Furthermore, environmental energy strongly depends on the weather and season, and its performance has obvious differences between day and night. Energy variations usually limit the feasibility of long-term and wide-ranging operations of these systems. Therefore, there is an urgent demand to develop a sustainable power source that can supply sufficient power to wireless sensors in remote locations while requiring less maintenance and low costs. Recently, much effort has been put into creating low-cost, eco-friendly energy options. Bioenergy [2] is a type of renewable energy derived from biological sources and can be an alternative, naturally-occurring energy source for wireless sensors. Its use can potentially provide a consistent, continuing energy supply. Microbial fuel cells (MFCs) are promising energy solutions for ubiquitous wireless sensing. In 1911, Potter published one of the first papers on electricity generation by bacteria [3]. Today, MFCs are receiving more attention because they are a potential part of the solution to our energy demands and could provide a clean and renewable source of energy. The MFC can produce power continuously as long as the bacteria are alive and active. However, current applications of MFCs are limited because of their low power density level of several hundred μW/cm2 [4]. Recently, much effort has been made toward the development of MFCs with high output power by cultured microbes, improved mediators, such as potassium ferricyanide [5] and thionine [6], and nutritionrich substrate for bacteria incubation. However, the mediators are usually toxic and the preparation processes are costly. Therefore, eco-friendly and low-cost MFCs are still in urgent demand for a large volume of applications. Our Earth is a kind of energy storage device that absorbs energy from sunlight to maintain the ecosystem. In addition

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to reflection and radiation from the surface of the Earth, about 70% of solar energy is absorbed by the atmosphere and by the planet’s surface. In other words, the organic matter in subsurface environments and aquatic sediments represents a large potential source of energy. MFCs using sea water have been demonstrated to power deployed sensors in the water [7], [8]. Similar to seawater, soil houses bacteria that can form a self-contained energy system. Through biochemical reactions from the activities of microorganisms, the energy in the soil can be released as electricity and heat. Soil can be utilized as a medium for building an MFC, forming a sustainable source for small electrical apparatuses. Accessibility, renewability, and portability make soil a feasible energy source for remote environment monitoring, especially for places lacking electrical infrastructures. The findings regarding soil energy may inspire intensive research interest and rapid progress in the development of self-powering sensor systems. However, the output voltage of a soil MFC is several hundred millivolts, which is insufficient to drive off-the-shelf electronics directly. Therefore, the low-power electronics and high-efficiency power management interface circuitry are challenges for developing practical applications of MFCs. Our previous work demonstrates a simple temperature and moisture environment sensing system with a micro-display using soil energy [9]. In this paper, we focus on the detail modeling of the energy cell and low-power electronic interface design for self-powering wireless sensor systems that exploit soil energy. The paper is organized as follows. First, we investigate the detailed characteristics of a soil cell using an electrical circuit model. A self-powering wireless temperature and moisture sensing system using only soil energy for remote environment monitoring is demonstrated. The theory of operation and characteristics of soil energy are described in Section II. Section III shows the implementation of the proposed selfpowering wireless moisture and temperature system using soil energy. The experimental results are shown in Section IV. Finally, a brief conclusion is provided in Section V.

IEEE SENSORS JOURNAL, VOL. 15, NO. 7, JULY 2015

Fig. 1. Electricity conversion from microbial reactions for powering circuits.

Anodic electrode potential is developed by the oxidation of electrons from the bio-reaction of microorganisms surround the electrodes. On the other hand, an oxidation reduction process occurs in the cathode electrode. In the oxidationreduction process, bacteria convert chemical energy to electrical energy. Typically, the reactions happening in the electrodes are shown as follows, using acetate as an example substrate: At the anodic electrode, C H3C O O − + 2H2 O → 2C O2 + 8e− + 7H +

(1)

while at the cathode electrode, O2 + 4e− + 4H + → 2H2 O.

(2)

Soil is the most spatially complex stratum on Earth, containing minerals and many organisms, such as bacteria, fungi, algae, protozoa, nematodes, and earthworms. Some bacteria in the soil are known to generate electricity (exoelectrogens) without the provision of an exogenous mediator [10]. These bacteria include Geobacter sulfurreducens [11], Rhodoferax ferrireducens [12] and Shewanella [13], each of which oxidizes the carbon source to transfer electrons without a mediator and derive energy for growth in the process.

The carbon dioxide and water, with a concomitant production of electricity as a by-product, are generated during the electrochemical reactions of bacteria and the substrate. The extra electrons can be induced by electrodes to the external load or energy storage elements, e.g. a battery or super capacitor. The soil energy can be an alternative energy source to remedy the environment and energy endeavors. Recently, the chemical-to-electricity conversion processes from bacteria are utilized to establish microbial fuel cells [14]. However, variations in the operating conditions, such as electrode materials, temperature, moisture, and MFC architecture, affect the output power of a soil energy cell. An electrical circuit model is needed for understanding the characteristics of a soil cell and to help with the electrical interface design. The effects of electrode materials, salt, and water contents in the soil cell are compared and verified with experimental results in the following sections.

A. Operation of Soil MFCs

B. Electrical Circuit Model of a Soil Energy Cell

Fig. 1 shows a conceptual diagram for powering electronic circuits using a microbial fuel cell (MFC). Bacteria in the soil act as an inexpensive and self-renewable catalyst for electrochemical oxidation of organic compounds, such as acetate, ethanol, and pyruvate, to carbon dioxide, electrons, and protons with metal electrodes as the electron acceptor.

The electrical properties of the soil are affected by the type of soil, density, operating frequency, water content, and soluble salts and minerals. Generally, soil is modeled as a parallel RC network of which the component values depend on the properties of the soil [15], [16]. The equivalent circuit provides insights for optimizing the MFC design and enhancing the

II. C HARACTERIZATION OF THE S OIL E NERGY C ELL

LIN et al.: SELF-POWERING WIRELESS ENVIRONMENT MONITORING SYSTEM USING SOIL ENERGY

Fig. 2.

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Electrical circuit model of a soil cell.

Fig. 4.

Fig. 3. Measured open-circuit output voltage of a D-size soil cell with various electrode materials.

output power. Fig. 2 shows the equivalent electrical circuit of a soil MFC. The low-frequency internal impedance of a soil MFC can be modeled using electrode resistance (Re ), charge transfer resistance (Rc ), double layer capacitance (Cd ), and substrate resistance (Rs ). The electrode resistance represents the intrinsic metal resistance, which relates to the contact area, material, surface roughness, and the rustiness of the electrodes. The charge transfer resistance corresponds to the electron transfer rate between the electrode metal and the soil substrate. The charge transfer rate depends on the kind of microbial reaction and the concentration of the reactants. It can vary largely due to the reaction media and the environment. The substrate resistance represents the resistance offered by the soil. The double layer is the charge separation between the electrode and the soil or across the bacterial membrane to maintain the charge motive force for their energy metabolism. The double layer can be modeled as a capacitor in the electrical circuit. The circuit model can help analyze the electrical characteristics of a soil energy cell and optimize the output power. C. Electrode Materials and Cell Potential Electrode materials directly influence the oxidation and reduction potentials and the charge transfer rates between electrodes [17]. The electrode materials need to have strong thermodynamic and kinetic responses, assuring that interface molecular interactions are fast enough to release oxidant electrons. Fig. 3 shows the measured open-circuit output voltage (Vsoil ) of soil cells with a variety of

Diagram of a Zinc-C soil cell.

electrode materials. The soil cell with Zinc-Carbon electrodes can attain a maximum open-circuit potential of 1.3 V, which is enough to power up low-power electronics using advanced CMOS technologies. From measurement and observation, the cell potential only depends on the electrode materials and does not vary largely with electrode space, surface area, or types of soil substrate. Fig. 4 shows the dimensions of a D-size Zn-C soil cell. The diameter of the Zinc crust is 34 mm, the height is 61 mm, and the diameter of the carbon electrode is 7 mm, creating a separation of 13 mm between electrodes. D. Substrate Impedance The total output power of the MFC is mainly limited by the high internal impedance. Soil contains a matrix of salinity, moisture, metals, and minerals that facilitate the conduction of electricity. The formation of a soil can be categorized by the content of its clay and sands. Generally, sands have the lowest conductivity, silts have a medium conductivity, and clays have the highest conductivity. The soil resistance is modeled as Rs in the electrical circuit model. In addition to reducing the internal resistance, a conjugate matching between the energy cell and the load is necessary to maximize the output power. Fig. 5 shows the measured output voltage and power of a D-size Zn-C soil cell at a variety of load impedance. The soil cell has the peak output power of 60 μW at a load impedance of around 2 k, which is close to the internal impedance of the fabricated D-size soil cell. At the small load impedance, the cell is current-limited; at the large load impedance, the cell becomes voltage-limited. Fig. 6 shows the measured output voltage and output power of two in-series and in-parallel soil cells at various load impedances. The in-series cell has high internal impedance, and thus, the peak output power occurs at the high load impedance. On the other hand, the in-parallel cells can provide large output current at a small load impedance where the output voltage does not reach the maximum electrode voltage potentials. In addition, stacking multiple cells in series often

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IEEE SENSORS JOURNAL, VOL. 15, NO. 7, JULY 2015

Fig. 7.

Fig. 5. Measured (a) output voltage and (b) output power of a D-size Zn-C soil cell versus load impedance.

Fig. 8.

Measured output power versus salt contents.

Measured output power versus soil humidity at a load of 2 k.

of 0.1 g, 0.2 g, and 0.3 g. The peak output power of the soil cell increases from 60 μW to 95 μW when 0.3 g of salt is added to the soil. The output power increases until the substrate resistance is not the dominant factor for the internal resistance of the soil cell. E. Effect of Water Content in the Soil

Fig. 6. Measured output power of two D-size Zn-C soil cells in series and in parallel versus load impedance.

causes voltage reversal due to the mismatch among cells and opposite polarity in the electrodes, thereby affecting the overall performance of the cell [18], [19]. Therefore, the soil cells in parallel provide higher output power at low load resistance than the soil cells in series. Some soil types are better able to conduct electricity than other soil types simply because their matrix contains higher percentages of certain minerals and salts that expedite the electrochemical reaction in the soil. Therefore, to boost the output power, salt, which enhances the conductivity of the soil substrate, can be added to the cells. In this way, the substrate resistance is reduced effectively, and thus, the output power increases. For example, conductive salt can be added to the soil cell to boost the output power. Fig. 7 shows the measurement results of the D-size soil cell with added salt

The electrical conductivity of soils varies depending on the amount of water held by soil particles. The higher water content in the soil lowers the substrate resistance and can accelerate the microbial reaction. Fig. 8 shows the measured results of the output power of a D-size soil cell at a load of 2 k in relation to the humidity. The output power and voltage of a soil cell drops as the water content in the soil is reduced; the output power is saturated even if the water content increases since the electron transfer rate from the membrane of the electrogenous bacteria reaches its maximum. F. Long-Term Response Fig. 9 shows the measured output power of a D-size Zinc-C soil cell over six days. Initially, the output power increases with the continuous growth of biofilm around anode electrodes. After 15 hours, the output power is stable since the net biofilm growth slows down or even stops. The output power drops slowly later on because the water contents of the soil cell evaporate over time. Therefore, to extend the operation time, an encapsulated cell is used to decrease the evaporation rate. In addition, the energy can be recovered quickly while

LIN et al.: SELF-POWERING WIRELESS ENVIRONMENT MONITORING SYSTEM USING SOIL ENERGY

Fig. 9.

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Measured output power of a soil cell for six days.

Fig. 12. (a) Architecture of the humidity sensor readout IC. (b) Schematic of the voltage-regulated RC oscillator.

Fig. 10.

Fig. 11. system.

Measured output power and voltage response to adding water.

and a Bluetooth low-energy transceiver with embedded temperature sensor. The embedded microcontroller adjusts the on/off duty-cycles of wireless data transmission to save power and controls the output power of the Bluetooth transmitter to accommodate the communication ranges for different applications. The output power of a wireless transmitter can be adjusted from −20 dBm to 4 dBm. The data from the temperature sensor is sent to the microcontroller for data processing. The microcontroller periodically wakes up the sensor and wireless transmitter only at a short time interval. In addition, a synchronous loop is added to ensure that the microcontroller can capture the correct sensor data.

System architecture of the proposed wireless environment sensor

the water is added to the soil cell without a biofilm generation phase. Fig. 10 shows the response of power recovery after watering the soil cell. The output power increases rapidly after adding water to the dry soil and then the power will saturate to a voltage at the reaction equilibrium. III. D ESIGN OF W IRELESS T EMPERATURE AND A IR M OISTURE S ENSING S YSTEM A. Architecture of the Proposed Wireless Environment Monitoring System To demonstrate the potential applications of the soil cells, we designed and fabricated a wireless temperature and air moisture sensing system on a PCB. Fig. 11 shows the architecture of the proposed self-sustaining wireless temperature and air moisture sensor system. The system includes a DC-DC converter, low-power microcontroller, air humidity sensor, custom capacitive humidity sensor readout IC,

B. Capacitive Humidity Sensor Readout Interface Since the commercial humidity sensor system is powerhungry, a custom low-power capacitive sensor readout IC is employed to convert the humidity-caused capacitance deviations to frequency deviations. The readout IC includes a regulated RC oscillator and a DC-DC voltage boosting charge pump circuitry, shown in Fig. 12 (a). The input voltage from a soil cell is pumped to 1.8 V to supply the capacitive readout interface and avoiding breakdown of advanced transistors. The capacitive sensor readout circuitry is shown in Fig. 12 (b). The regulated RC oscillator [20] is used to eliminate the frequency instability caused by device mismatch, noise, and supply as well as temperature variations. The time constant of the RC oscillator is derived as (1 + K sw )(2 − K sw ) (3) T = RC ln( K sw (1 − K sw ) Vsw K sw = V D D_reg where Vsw is the switching threshold voltage and VDD_reg is the regulated supply voltage. The time constant is related

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Fig. 14. system.

Photograph of the soil-powering wireless environment monitoring

Fig. 13. (a) Schematic of charge pump. (b) Four-phase clock timing diagram.

to the R and C values but is less affected by the switching threshold voltage variations caused by the device size and doping deviations. To reduce the effects of supply voltage fluctuations from the soil cell, a negative feedback loop, including transistors (M1 – M3), is employed to regulate the supply voltage. A PTAT current bias circuitry is adopted to eliminate the temperature-caused frequency drifts. The capacitive humidity sensor is connected with C1 in parallel, and the oscillation frequency of the RC oscillator changes with capacitance deviation from the sensor. Therefore, the humidity is decoded by the frequency deviations. C. Four-Phase DC-DC Charge Pump The open-circuit output voltage of a Zn-C soil cell is around 1 V and drops as the cell is loaded. Therefore, a DC-DC boosting converter is required to supply enough voltage to the submicron CMOS circuits. A four-phase charge pump [21] is adopted for lowering the threshold voltage drops when compared to the conventional Dickerson’s charge pump. Fig. 13(a) shows the schematic of the DC-DC converter. A low-voltage ring oscillator using low-Vt transistors is directly powered up from the soil cell. The lowest supply voltage to operate the oscillator is 300 mV. A phase generator is employed to create four non-overlapping clock signals that drive the charge pump in a sequence to compensate the threshold voltage loss of the pass transistors. Fig. 13(b) shows the timing diagram of the four-phase clock signals. The four-stage charge pump circuitry consists of pass transistors (M1 – M4), input capacitors (Cp1 – Cp4 ), boosting transistors (Ma1 – Ma4 ), and boosting capacitors (Ca1 – Ca4 ). Instead of diode-connected MOS transistor, Ma1 – Ma4 are added to boost up the gate voltage of M1 – M4 by the gate-controlled signals (Vp1 and Vp3 ) before the charge transfer phases (Vp0 and Vp2 ).

Fig. 15.

Micrograph of the humidity sensor readout chip.

The gate bias levels of M1 – M4 are shifted to the voltage level of the prior stages and then the gate voltages are boosted up again by the amplitude of Vp0 and Vp2 , making the passtransistors into the triode region. Theoretically, the output voltage of the four-phase charge pump is IT (4) C where Vin is the input voltage of charge pump, N is the number of stages, VA is the amplitude of clock signal, I is the output current of charge pump, and T is the clock period of Vp1 and Vp3 . In addition, transistor (M5) is used in the last stage to reduce the reverse leakage current from the output to the charge pump. Therefore, the efficiency of the charge pump is improved in terms of low on-resistance of the pass transistors and low reverse current from output node to the charge pump. The simulated peak efficiency of the four-phase charge pump is 67% at an input voltage of 0.5 V. Vout = Vin + N · V A − N ·

IV. I MPLEMENTATION AND E XPERIMENTAL R ESULTS Fig. 14 shows the proposed wireless environment monitoring system. The system includes a humidity sensor readout IC, a microcontroller, and a Bluetooth LE (BLE) transceiver with an embedded temperature sensor. The humidity sensor (Parallax HS 1101) is connected to the readout circuitry chip, which is fabricated using a 0.18 μm CMOS process. Fig. 15 shows the die micrograph of the humidity sensor readout circuitry. The chip size is 1.6 mm2 . The system can be

LIN et al.: SELF-POWERING WIRELESS ENVIRONMENT MONITORING SYSTEM USING SOIL ENERGY

Fig. 16. Measured output frequency versus output capacitance of the air humidity sensor.

Fig. 17.

Measured air humidity results over seven hours.

Fig. 19.

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Measured temperature results received by a smart phone.

energy storage capacitor followed by the DC-DC converter. The capacitor can be charged back to the 3.15 V regulated voltage by the soil cell. The wireless transceiver is activated for about 0.6 seconds at every 10-second time interval. The system can wirelessly transmit temperature data to the terminal device at a distance of 3-10 m, depending on the output power of the transmitter. The measured, wirelessly transmitted temperature results, as read from a smart phone, are shown in Fig. 19. The temperature resolution of the embedded temperature sensor is 1 °C. The prototype can provide a low-cost and eco-friendly energy solution for ubiquitous, wireless environment monitoring. V. C ONCLUSION

Fig. 18. Measured voltages of the energy storage capacitor during the wireless sensor system operation.

powered directly by a D-size soil cell. The power consumption of the sleep-mode microcontroller, the humidity sensor readout IC, and the BLE transceiver with the active microcontroller are 17 μW, 3 μW, and 1 mW (on-state, −20 dBm output power in the advertised mode), respectively. Fig 16 shows the measured results of the frequency changes with the various capacitances and the relation to the relative air humidity. The on-chip capacitance is 20 pF, and the free-running oscillator frequency is 7 kHz without any load. The output period is linearly proportional to the sensing capacitance. The readout circuitry can detect the capacitance range between 160 pF and 200 pF. A commercial air humidity sensor is employed to monitor the moisture changes according to the sensing capacitance variations. Fig. 17 shows the measurement results of the humidity over seven hours in the evening. Fig. 18 shows the measured voltage drops during wireless data transmission. In the measurement, a 1 mF is used as the

This paper presents an autonomous, wireless temperature and moisture sensor system using low-cost and widely-accessible soil energy. The fabricated D-size (55.8 cm3 ) Zn-C soil cell can supply an average power of 60–100 μW continuously without special treatments. Compared to other renewable energies, such as solar and tidal energy, soil energy is easily accessible, insensitive to environment changes, and does not require expensive infrastructure. The soil-powered wireless temperature and air moisture monitoring system, including a Bluetooth-LE transmitter, microcontroller, and a low-power capacitive sensor readout interface integrated with a DC-DC converter, has been demonstrated herein. The system can be further utilized for remote field experiments and environment monitoring in energy-constrained areas to avoid frequent battery replacement. To improve the output power of a soil cell, cultured bacteria and prepared soil substrate can be used. The new technology can enable promising applications in environmental monitoring and green electronics. R EFERENCES [1] H.-C. Lee, A. Banerjee, Y.-M. Fang, B.-J. Lee, and C.-T. King, “Design of a multifunctional wireless sensor for in-situ monitoring of debris flows,” IEEE Trans. Instrum. Meas., vol. 59, no. 11, pp. 2958–2967, Nov. 2010. [2] C. Himes, E. Carlson, R. J. Ricchiuti, B. P. Otis, and B. A. Parviz, “Ultralow voltage nanoelectronics powered directly, and solely, from a tree,” IEEE Trans. Nanotechnol., vol. 9, no. 1, pp. 2–5, Jan. 2010. [3] M. C. Potter, “Electrical effects accompanying the decomposition of organic compounds,” Proc. Roy. Soc. London Ser. B, Contain. Papers Biol. Character, vol. 84, no. 571, pp. 260–276, Sep. 1911.

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[4] Y. Fan, H. Hu, and H. Liu, “Enhanced Coulombic efficiency and power density of air-cathode microbial fuel cells with an improved cell configuration,” J. Power Sour., vol. 171, no. 2, pp. 348–354, Jul. 2007. [5] L. Wei, H. Han, and J. Shen, “Effects of cathodic electron acceptors and potassium ferricyanide concentrations on the performance of microbial fuel cell,” Int. J. Hydrogen Energy, vol. 37, no. 17, pp. 12980–12986, Sep. 2012. [6] M. Rahimnejad et al., “Thionine increases electricity generation from microbial fuel cell using Saccharomyces cerevisiae and exoelectrogenic mixed culture,” J. Microbiol., vol. 50, no. 4, pp. 575–580, Aug. 2012. [7] A. Meehan, G. Hongwei, and Z. Lewandowski, “Energy harvesting with microbial fuel cell and power management system,” IEEE Trans. Power Electron., vol. 26, no. 1, pp. 176–181, Jan. 2011. [8] C. Donovan, A. Dewan, D. Heo, and H. Beyenal, “Batteryless, wireless sensor powered by a sediment microbial fuel cell,” Environ. Sci. Technol., vol. 42, no. 22, pp. 8591–8596, Oct. 2008. [9] F.-T. Lin, J.-C. Hsieh, F.-C. Wen, W.-K. Wang, H.-C. Lee, and Y.-T. Liao, “Towards a self-sustained moisture and temperature monitoring system using soil energy,” in Proc. IEEE Sensors, Nov. 2013, pp. 1–4. [10] E. Parra and L. Liwei, “Microbial fuel cell based on electrodeexoelectrogenic bacteria interface,” in Proc. IEEE 22nd Int. Conf. Micro Electro Mech. Syst., Jan. 2009, pp. 31–34. [11] D. R. Bond and D. R. Lovley, “Electricity production by Geobacter sulfurreducens attached to electrodes,” Appl. Environ. Microbiol., vol. 69, no. 3, pp. 1548–1555, 2003. [12] Z. D. Liu, Z. W. Du, J. Lian, X. Y. Zhu, S. H. Li, and H. R. Li, “Improving energy accumulation of microbial fuel cells by metabolism regulation using Rhodoferax ferrireducens as biocatalyst,” Lett. Appl. Microbiol., vol. 44, no. 4, pp. 393–398, 2007. [13] V. J. Watson and B. E. Logan, “Power production in MFCs inoculated with Shewanella oneidensis MR-1 or mixed cultures,” Biotechnol. Bioeng., vol. 105, no. 3, pp. 489–498, 2010. [14] Y. Yuan, S. Zhou, and L. Zhuang, “A new approach to in situ sediment remediation based on air-cathode microbial fuel cells,” J. Soils Sediments, vol. 10, no. 7, pp. 1427–1433, 2010. [15] K. K. Singh, N. K. Chasta, and M. S. Baghini, “Experimental electrical modeling of soil for in situ soil moisture measurement,” in Proc. Int. Symp. Electron. Syst. Design (ISED), Dec. 2013, pp. 123–127. [16] S. Sekioka, M. I. Lorentzou, M. P. Philippakou, and J. M. Prousalidis, “Current-dependent grounding resistance model based on energy balance of soil ionization,” IEEE Trans. Power Del., vol. 21, no. 1, pp. 194–201, Jan. 2006. [17] J. Wei, P. Liang, and X. Huang, “Recent progress in electrodes for microbial fuel cells,” Bioresour. Technol., vol. 102, no. 20, pp. 9335–9344, Jul. 2011. [18] A. Gurung and S. E. Oh, “The improvement of power output from stacked microbial fuel cells (MFCs),” Energy Sour., A, Recovery, Utilization, Environ. Effects, vol. 34, no. 17, pp. 1569–1576, Jun. 2012. [19] I. Ieropoulos, J. Greenman, and C. Melhuish, “Improved energy output levels from small-scale microbial fuel cells,” Bioelectrochemistry, vol. 78, no. 1, pp. 44–50, 2010. [20] D. Griffith, P. T. Roine, J. Murdock, and R. Smith, “17.8 A 190 nW 33 kHz RC oscillator with ±0.21% temperature stability and 4 ppm long-term stability,” in IEEE Int. Solid-State Circuits Conf. Dig. Tech. Papers (ISSCC), Feb. 2014, pp. 300–301. [21] Y.-C. Shih and B. P. Otis, “An inductorless DC–DC converter for energy harvesting with a 1.2-μW bandgap-referenced output controller,” IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 58, no. 12, pp. 832–836, Dec. 2011.

Yu-Chun Kuo received the B.S. degree in electronics engineering from Chun Yuan Christian University, Taoyuan, Taiwan, in 2012. He is currently pursuing the master’s degree at the Department of Electrical Engineering, National Chung Cheng University, Chiayi, Taiwan. His research interests include power management circuit and systems.

Fu-To Lin (S’12) received the B.S. degree from the Department of Electrical Engineering, National Chung Cheng University, Chiayi, Taiwan, in 2014. He is currently pursuing the M.S. degree at the Department of Electrical Engineering, Institute of Biomedical Engineering, National Chiao Tung University, Hsinchu, Taiwan. His research interests include low-power circuits for wearable and implantable biomedical applications.

Jen-Chien Hsieh received the B.S. degree in electrical engineering from National Chung Cheng University, Chiayi, Taiwan, in 2014, where he is currently pursuing the M.S. degree at the Department of Electrical Engineering. His primary research interest is in mixed-signal circuit design.

Hsi-Yuan Tsai received the B.S. degree in communication engineering from National Chung Cheng University, Chiayi, Taiwan, in 2014, where he is currently pursuing the M.S. degree at the Department of Communications Engineering. His primary research interest is in hardware and software design for BLE applications.

Yu-Te Liao (S’03–M’11) received the B.S. degree in electrical engineering from National Cheng Kung University, Tainan, Taiwan, in 2003, the M.S. degree in electronics engineering from National Taiwan University, Taipei, Taiwan, in 2005, and the Ph.D. degree in electrical engineering from the University of Washington, Seattle, WA, USA, in 2011. In 2011, he joined the Department of Electrical Engineering, National Chung Cheng University, Chiayi, Taiwan, as an Assistant Professor. He is currently an Assistant Professor with the Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan. His research interests are in the design of low power RF integrated circuits, integrated sensors, and biomedical circuits and systems.

Huang-Cheng Lee (SM’12) received the Ph.D. degree from National Tsing Hua University, Hsinchu, Taiwan, in 2010. He has been an Assistant Professor with the Department of Communications Engineering and Electrical Engineering, National Chung Cheng University, Chiayi, Taiwan, since 2011. He is currently an Associate Editor of the IEEE T RANSACTIONS ON I NSTRUMENTATION AND M EASUREMENT in 2015. He has also been in the industry since 2000, and has a wide breadth of experience in designing personal digital assistant/cellular phones and low-power embedded systems. His research topics are mainly related to wireless sensor network, Internet of Things, and embedded system, in particular, for natural environment monitoring, disaster monitoring, and energy conservation.

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A Reliable Wireless Sensor System for Monitoring Mechanical Wear-Out of Parts.pdf. A Reliable Wireless Sensor System for Monitoring Mechanical Wear-Out of ...

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IJRIT International Journal of Research in Information Technology, Volume 2, ... 1PG student, Electronics Department, Shri Sant Gajanan Maharaj College of ...

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classroom, involving 10 personal computers, is analyzed. Section 6 reviews related ... IP address: this is the node's Internet Protocol address. The IP address ...

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Hadoop is a MAD system that is becoming popular for big data analytics. An entire ecosystem of tools is being developed around Hadoop. Hadoop itself has two ...

Energy-Efficient Surveillance System Using Wireless Sensor Networks
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Keywords: self sufficiency, renewable, solar, energy, appropriate technology, stirling engine, CSP, ... 'Wireless' in this context describes the independence ... For comparison, three different consumption scenarios have been defined: Scenario ...