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Abstract – Now a days, Wireless Sensor Networks (WSNs) are
attractively being used for multiple purposes due to their
Fig. 2 Overview of WSNs Applications [2], [10]
Currently, WSNs are suffering from energy consumption
issues. Since Wirel...
Fig. 3 Classification of WSNs' Techniques for better Energy Consumption
the Sink node or base station.
Using these techn...
are used to increase the amount of energy being harvest. For
RF energy harvesting, RF Identification (RFID) system
[20], [23],
Near 30% a...
blood circulation, body temperature, frequency/pitch of
voice, walking/jogging/running movement – by using shoe
mounted ...
model to determine the amount of excessive energy for a
given period of time. M. Kang, S. Jeong, I.Yoon et al.
proposed ...
of energy as compared to PEHT but its efficiency is limited
as it is dependent upon the temperature difference ∆T. This
An ideal energy buffer would be the one that can save
energy in abundance without ...
level of 10MΩ output load at 1V output voltage shows
working rate having the efficiency of 25.7%. The authors
environment, sunlight energy is selected as an energy
harvesting source. Though solar energy have some
drawbacks that i...
purpose pyroelectric device is attached to the outer side of the
beaker having various chemical exothermic reactions. T...
function, an energy aware interface (EAI) in order to deal
with the dissimilarity between the energy generated and
harvesting scenario is to harvest as many energy as possible
from multiple sources. So this requirement leads to the
[12], [48]–[50], [53]–[57],
difference and most
commonly 40
[52] possible
Radio Frequency Based...
Westhoff, “Wireless sensor networks for flash-flood alerting,”
Proc. Fifth IEEE Int. Caracas Conf. Devices, Circuits Sy...
Electron., vol. 58, no. 9, pp. 4424–4435, 2011.
[55] Y. Shi et al., “A novel self-powered wireless temperature sensor
Topology and Design Optimization Method for Wideband
Piezoelectric Wind Energy Harvesters,” IEEE Trans. Ind.
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Energy Harvesting Techniques in Wireless Sensor Networks – A Survey


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It is a Self effort done under the supervision of my Respected Supervisor Dr. A Rehman, to surveyed out all the techniques for Energy harvesting in WSNs. Harvesting Systems are basically subdivided into two types. One in which ambient energy is converted to required electrical energy directly without any storage and the other is where storage of converted energy is required before supplying. So for these sub-systems different energy harvesting techniques are proposed which are Radio Frequency based, solar based, thermal based, flow based from source of ambient environment and from external sources of mechanical based & human based. Flow based are further classified into wind based and hydro based. Each energy harvesting technique’s source has its own capability to harvest energy and can effectively overcome the issues of energy consumption.

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Energy Harvesting Techniques in Wireless Sensor Networks – A Survey

  1. 1. 1 Abstract – Now a days, Wireless Sensor Networks (WSNs) are attractively being used for multiple purposes due to their extensively beneficial nature. A WSN contains sensor nodes, a sink node and uses electromagnetic radio waves to establish connection with internet or to form any other network. Most commonly WSNs are being used to sense atmospheric conditions, movement recognitions, security purposes, object tracking, fire detection etc. Currently, WSNs are suffering from energy consumption issues. Since they are deployed in abundance at very unfriendly and difficult places so in case of any loss of energy supply it is very hectic task to re-supply or recharge the batteries that are being used to supply energy to the Wireless Sensor nodes. As the sensor nodes need to be more functional so to achieve it, the life of the WSNs and their sensor nodes need to be extended either by reducing the energy consumption factor by disabling all the subsystems in certain mode or by introducing some mechanisms to harvest energy either from external sources or ambient surroundings. Disabling the subsystems is also proven not so beneficial hence a need to introduce an appropriate energy harvesting system aroused. Harvesting Systems are basically subdivided into two types. One in which ambient energy is converted to required electrical energy directly without any storage and the other is where storage of converted energy is required before supplying. So for these sub-systems different energy harvesting techniques are proposed which are Radio Frequency based, solar based, thermal based, flow based from source of ambient environment and from external sources of mechanical based & human based. Flow based are further classified into wind based and hydro based. Each energy harvesting technique’s source has its own capability to harvest energy and can effectively overcome the issues of energy consumption. Index Terms – Micro electro-Mechanical Systems (MEMS), Mechanical Harvesting, piezoelectric harvesting, Radio Frequency (RF), Seebeck Effect, Solar & Thermal Harvesters, Wind and Hydro Harvesters, Wireless Sensor Networks (WSNs). I. INTRODUCTION ecently, the wild usage of sensing and wireless based communication technology has enabled the development of networks of this technology. WSNs are attractively being used for multiple purposes due to their extensively beneficial nature, mostly because of their rapidly growing use in Micro electro-Mechanical Systems (MEMS) [1], which introduced Farwa A. Hannan was born in Faisalabad and is now a student of MSCS in Fast National University of Computer and Emerging Sciences, CFD campus, Pakistan (Email: smart sensors that are small in size, have limited processing and computing resources, not so expensive, can sense, measure and collect information from the surroundings and send the sensed data to the user [2]. Wireless Sensor Networks are of two types – structured and unstructured. In Structured one, sensor nodes are deployed randomly in ad hoc way in abundance and then left unattended to do monitoring while in the later one, some/fewer sensors are deployed according to pre-defined plan and due to less abundance of sensor nodes, maintenance and management costs are reduced. A WSN contains a collection of sensor nodes (few tens to thousands), a sink node which is also known as Base station that provide a human interaction platform which can be accessed remotely by the user, electromagnetic radio waves to establish connection with internet or to form any other network and a remote location to send the processed data as illustrated in Fig. 1. Wireless sensor nodes contain limited storage and computational capacity and require low energy consumption to let themselves work for longer time span [3]. Smart sensor node contains memory, power supply, sensor (thermal, biological, chemical, mechanical, magnetic), processor, radio and an actuator which is used to control the different components of a system like controlling/actuating different sensing devices [2]. Most commonly WSNs are being used to sense movement, atmospheric conditions, for security purposes, object tracking, fire detection etc. WSNs have large number of applications like surveillance, military target tracking[4], hazardous environment exploration, natural disaster relief [5], biomedical health monitoring [6], [7] and detection of earthquakes/volcanos or other vibrations of the earth etc. [8]. Multimedia WSNs have also been introduced in order to track or monitor any event in the form of audio/image/video etc. [9]. Fig. 2 gives the overview of the WSN’s applications. Fig. 1 General Architecture of a WSN Energy Harvesting Techniques in Wireless Sensor Networks – A Survey Farwa A. Hannan, Fast-NUCES R
  2. 2. 2 Fig. 2 Overview of WSNs Applications [2], [10] Currently, WSNs are suffering from energy consumption issues. Since Wireless Sensor nodes are containing three subsystems each – sensing subsystem, processing subsystem and wireless communication subsystems [11] so they consume efficient amount of power supply/energy and are deployed in abundance at very unfriendly and difficult places. Hence in case of any loss of energy supply it is very hectic task to re-supply or recharge the batteries that are being used to supply energy to the Wireless Sensor nodes. As the sensor nodes need to be more functional so to achieve it, the life of the WSNs and their sensor nodes need to be extended either by reducing the energy consumption factor by disabling all the subsystems when the Wireless Sensor nodes are in sleep mode/inactive mode or introducing some mechanisms to harvest energy either from external sources or ambient surroundings. Disabling the subsystems is also proven not so beneficial because mostly sensor nodes require continuous power supply for processing data hence a need to introduce an appropriate energy harvesting system aroused[12]. Schemes to make the sensor nodes of a network less energy consuming are introduced in upcoming paragraphs. In [13] WSNs are made energy efficient by introducing energy efficient routing scheme. As the sensor nodes have limited energy supply so they need to be working in a low power operation mode. As the nodes route data to each other in order to sync it at sink node so according to this scheme when a node is in low energy mode it alerts other nodes to stop routing data to it until it reaches the maximum level of energy again. The authors in [14], [15] proposed Energy Efficient Routing in Wireless Sensor Networks Through Balanced Clustering by introducing Equalized Cluster Head Election Routing Protocol (ECHERP) scheme. In very large WSNs, nodes are divided/ combined in clusters and a cluster head is selected which gathers the data of its cluster so in proposed ECHERP and Energy Efficient Clustering Scheme (EECS) schemes a cluster head is selected randomly or the one having maximum amount of energy which is enough to perform further operations. Hence in this way energy consumption is reduced by making routing energy efficient. In [16] to reduce energy consumption in WSNs, schemes of Duty Cycling, Data driven and Mobility are introduced. In duty cycling approach the radio transceiver is turned off when it is not in duty/operational mode. As the radio transceiver is used to send or receive data between nodes so when data transferring or receiving is not required, radio transceiver is put in sleep mode which will resume its working when the new data is ready to send or receive. This kind of mechanism is termed as duty cycling. While data driven scheme is related to stop the transmission/ reception of redundant information. Eliminating the transmission/ reception of redundant information or such information which is not required, lead to less energy consumption. Introducing the mobile sensor nodes reduce energy consumption to a great extent. In the static sensor network, data packets are transferred by following a multi-hop path which can lead to produce an increased load on some nodes and hence more energy is consumed but by introducing mobile nodes, the node's load can be reduced because in this scenario mobile nodes will be able to collect data directly from the static ones and send it to
  3. 3. 3 Fig. 3 Classification of WSNs' Techniques for better Energy Consumption the Sink node or base station. Using these techniques no doubt energy consumption will be reduced but still one day the power supply will be completely consumed and will be needed to recharge. So in order to supply a continuous and long lasting power supply to the sensor nodes energy needs to be harvested from some cheap and continuous sources. Energy Harvesting is actually a mechanism of generating energy from the concerned network’s immediate surroundings to provide an un-interrupted or continuous power supply to the sensor nodes of the WSN. For this purpose Energy Harvesting Systems are basically subdivided into two types. One where ambient energy is directly converted to required electrical energy and the other is where storage of converted energy is required before supplying. So for these sub-systems different energy harvesting techniques are proposed namely Radio Frequency based Energy harvesting (RFEH), solar based Energy harvesting (SEH), thermal based Energy harvesting (TEH), Electric-field energy harvesting (EFEH), Magnetic Field Energy Harvesting (MFEH), flow based Energy harvesting (FEH) from source of ambient environment and from external sources of mechanically driven Energy harvesting (MDEH) & human based Energy harvesting (HEH). Flow based Energy harvesting techniques are further classified into wind based Energy harvesting (WEH) and hydro based Energy harvesting (Hydro EH) [12]. All these techniques are classified in Fig. 3. This paper explores the all the techniques (previous and latest) to harvest energy from ambient environmental sources, efficient elements for energy buffers, the sensor nodes/harvesters of each technique and the major open research challenges as well, which collectively make this paper unique. Until now only one latest survey paper related to multiple energy harvesting techniques exists which covers the research work mainly related to the harvesters of the energy harvesting techniques. It was accepted on 12 November 2015 and was written by Faisal Karim Shaikh and Sherali Zeadally. The rest of the paper is assembled as follows. Section II gives an explanatory review of the energy harvesting techniques. Section III discusses the appropriate storage elements for the appropriate energy harvesting technique. Section IV points out some major research challenges that are still unaddressed while Section V is related to results and discussion. Final in Section VI I've presented some concluding remarks as well. At the end, Section VII, VIII and IX is related to future work, acknowledgement and references respectively. II. TYPES OF ENERGY HARVESTING TECHNIQUES IN WSNS To harvest energy, different sources can be chosen by keeping in mind the requirement of energy and to generate power, suitable voltage level needed to be considered also. A. RFEH TECHNIQUE Harvesting Energy from Radio Frequency doesn’t involve any battery usage. This technique, by using some receivers (easily added to Circuit Board) like Powercast’s Powerharvester, harvest/receive electromagnetic waves or radio waves which are being broadcast from radio transmitters like smart phones, TV or radio broadcast stations, WIFI etc. and convert it into Direct current (DC) power supply [17] which after some conditioning/cleaning is continuously supplied to active sensor nodes/WSNs, in a defined schedule or when it is required. This technique gives the advantage of power distribution in a one to many fashion in which the power can be supply from one node to all other nodes that can communicate or sense the transmitter. If the power being harvest isn’t up to the required level then some power boosters like Multistage Villard Voltage Multiplier, Multistage Dickson Charge Pump etc. or multiple antennas
  4. 4. 4 are used to increase the amount of energy being harvest. For RF energy harvesting, RF Identification (RFID) system which read and captures information by using Radio Waves, is a RF energy harvesting (EH) solution which is available in the market [12]. This RF based mechanism can be used indoors and outdoors. Fig. 4 demonstrate the RF energy harvesting system for wireless sensor networks. This harvesting process starts with a given antenna that can fetch radiation waves/frequencies and harvest power from them. As this technique is capable of transferring the received radiation frequency signals into electricity/Direct current so it is a very effective, encouraging and favorable alternative solution to provide power supply to the energy constrained WSNs. The energy harvested by using RF Harvester can be utilized in recharging any low power device. With the increasing number of the wirelessly operating transmitters the RF based power/energy availability is also increasing. The RF based energy harvesting networks are now enormously being used in Wireless Body area Networks (WBANs), WSNs and wirelessly charging Systems (WCSs) Now a days most of the wireless portable devices are largely dependent on the battery power especially the nodes of WSN which require constant battery supply. Since TV, radio, cellphones and many other electric devices eject Radio frequencies/waves in the air continuously. Hence by utilizing these waves as an electric power supply one can easily recharge any device in any place. RFID technology is an example of the RFEH technique. In [18] the experimental results of the RF energy harvesting from the Radio Frequency electromagnetic waves are presented. The system design for this particular experiment consists of an antenna, voltage multiplier circuit, storage capacitor and a tuning circuit. Monopole, Micro strip patch and loop antennas are used for this experiment. The worst results were obtained using monopole antenna using which the system produced 10mV of storage capacitor in 4 days. While using Loop antenna the results were the best. The system using loop antenna produced 1V in 0 seconds and 1.25V in 20 seconds. Harvesting energy from RF waves has led to the development of the Ultra-low power wireless devices that can be developed for low maintenance applications like remote monitoring [19]. Fig. 4 RF based Energy Harvesting System Mechanism for WSNs The radio frequency based energy harvesting mechanism uses radioactive signals as a medium to take power/energy in Electromagnetic Radiation form, with a frequency range of 300GHz to 3 kHz. The other techniques to transfer energy wirelessly are Magnetic Resonance Coupling (MRC) - based on the usage of Evanescent Field/Wave coupling to produce electricity and transfer it between resonators and Inductive Coupling (IC) - based on Magnetic Field Coupling that transfers generated electrical energy between coils that produce electrical or mechanical resonance at the same frequency [20]. But both of these techniques shown in Fig. 5, work in the near region wireless transmission not in the farther ones so the coils or resonators used in these two techniques need to be placed as close to the transmitters & receivers as possible which is the reason of preferring RF based energy harvesting mechanism in case of mobile and remote charging due to the extra effort requirement on the alignment of the resonators/coils at each receiving and transmitting end in both the other mentioned techniques. Hence Radio Frequency based energy harvesting mechanism can be called as the Far-Field energy harvesting/transferring technique as well. The readers can refer to [21], [22] for more detailed explanation of wireless energy transfer techniques. The comparison between these three techniques is shown in Table 1 also elaborated in [23]. Fig. 5 Magnetic Resonance and Inductive coupling TABLE 1 COMPARISON OF DIFFERENT RF BASED WIRELESS ENERGY TRANSFER TECHNIQUES Wireless Energy Transfer (WET) Technique s Apps Field Efficiency % in respective Applicatio n Field Nature Year Radio Frequency Based [12], [21], [22], [23] WSNs, WBAN s Far- Field/ Regio n Over 50% at -5 decibel- mill watts Radioactiv e 2012 , 2014 , 2016 Inductive Coupling [20], [23], [24] RFID Near 57% at 508kHz Non- radioactive 2011 , 2014 , 2016
  5. 5. 5 Magnetic Resonance Coupling [20], [23], [24] plug-in hybrid electric vehicle (PHEV) & Smart phone's chargin g Near 30% at distance of 2.25m 90% at the distance of 0.75m Non- radioactive 2011 , 2014 , 2016 B. MDEH TECHNIQUE By utilizing electro-magnetic waves, Mechanical energy can be obtained from sources like vibrating structures i.e. vibrations produced by pressure, flow of air or water and can be termed as wind or hydro-electric energies. Generally, generation of electric energy from mechanical ones is accomplished by using piezoelectric or electromagnetic or electrostatic mechanisms. The mechanical strain can be converted to electrical voltage by utilizing piezoelectric effect. The mechanical strain can be obtained from seismic vibrations of low frequency, human motion etc. This effect can be obtained from human walking also [12]. Piezoelectricity is a crystal’s ability to produce electricity by applying mechanical stress. By the application of the mechanical stress upon crystal, the alignment of the electric charge of the dipoles occurs which lead to the electric polarization and produces electricity. Recently piezoelectric based heel strike units were developed in which small electric generators are installed that uses piezoelectric material to convert mechanical motion to electric power [24]. Piezoelectric mechanism can harvest electrical energy from mechanical energy of pressure, vibrations or force sensed by the sensors. By straining a piezoelectric material electrical energy converted from mechanical energy can be obtained. Piezoelectric harvester has a cantilever like structure. Its piezoelectric beam has a seismic mass attached. In the piezoelectric harvester, the piezoelectric material's strain do the charge separation resulting in the electric field and the required voltage/current/power which varies according to the change in strain and time [26]. Piezoelectric energy harvesting mechanism has lots of benefits like simple structure/less complexity, low cost, no interference of electro magnetism, efficiency of electromechanical conversion etc. [27]. In electrostatic energy harvesting technique required energy is produced by varying the capacitance of capacitor which depends upon vibrations. This harvester unlike piezoelectric harvester provides an initial voltage to the capacitance of the capacitor and as a result vibrations are produced by the external voltage application which lead to the change of the quantity of charges stored in capacitor. This process leads to the generation of electric current. Electromagnetic energy harvesting mechanism works on the electromagnetic induction principle of Faraday's law. By using a stationary magnet a magnetic field will be created and then the electricity can be produced by passing a magnetic mass through this field. But due to the enhanced size of the magnetic materials, it is a very hectic task to implement them in the sensor nodes [26], [27]. A magnetic spring based electromagnetic energy harvester consisting of a hollow tube with two magnets fixed at both ends and a magnetic stack moving inside is presented in [28] along with its design, modeling and experimental evaluation. A lot of electromagnetic generators have been introduced to harvest energy from the vibrations produced by the human motion. The authors in [28] mentioned that Rome et al. introduced an electromagnetic suspended load backpack which converted the mechanical energy obtained from the vertical movement of the carried load to electrical energy during the state of walking and an electromagnetic generator introduced by Saha et al. which can be placed in the rucksack and it had the capability of generating 300 microwatt to 2.46 mW as shown by the experimental results. Similarly Ylli introduced multi coil topology harvester that using a set of coils accelerate a magnetic stack upon the swing motion of the foot and produces 0.84mW. Vibrational energy is available in our surroundings in abundance like from different types of industrial & commercial machines, vehicles, railway structures etc. The ideology of vibration to electric energy production was proposed by Williams and Yates in 1996. Since then it is an attractive technique of producing energy and powering low power devices. In [29] using multiple nonlinear techniques a piezoelectric vibration energy harvester is presented. Using these techniques the shape of the piezoelectric material or cantilever is changed to nonlinear form to generate energy from varying vibrational frequency and the bandwidth is broaden. The multiple nonlinear effects including Duffing- spring effect, impact effect, pre- load effect, and air elastic effect can be achieved in this type of Harvester. In [30] a study on the feasibility of the Piezoelectric Harvesters such as MEMs, for Low-Level Vibrations in Wireless Sensor Networks is presented. According to this study piezoelectric harvester is such a harvester which transfers the mechanical energy to electrical energy by straining/deforming a piezoelectric material. This strain produces a charge separation across the device, which led to the production of an electric field that is proportional to the applied stress. C. HEH TECHNIQUE Living bodies have great resources of energy in the form of chemical, thermal and mechanical energies. These energies can be utilized to overcome the battery/rechargeable energy consumption problem so that long-term processing of the sensor nodes or wearable devices can be achieved [31]. WBAN is the most active application of wireless sensor networks which involve the sensor's implantation inside the human body for the betterment of health and quality of life. Apps of WBANs are shown in Fig. 6. WBAN is an interesting evolution of wireless sensor networks. In human based energy harvesting mechanism, Wireless Body Area Networks (WBANs) [32] are used that are basically implanted inside the human body and can generate energy through the change/movement of the finger position,
  6. 6. 6 blood circulation, body temperature, frequency/pitch of voice, walking/jogging/running movement – by using shoe mounted rotary harvesters [33] etc. Due to their installation inside the human body the lifetime of these sensor networks can be longer than the others and hence the reason that human based energy harvesting mechanism is more preferable [12]. Hence various techniques to harvest energy can be implemented and utilized to generate more energy in order to compensate energy consumption issues. Fig. 6 Applications of WBANs/HEH [34], [35] D. SEH TECHNIQUE Another source to harvest energy for WSNs is from sunlight or solar energy which is available in abundance and is affordable. Hence its utilization for generating electrical energy is a clean source. In this technique semiconductor materials like crystalline silicon (c-Si) in solar cells or solar panels, are used that harvest the solar rays into the direct current power supply. When the photons of sun light falls on the solar panel the separation of electron and holes occur due to the special manufacturing mechanism of the Solar Panel and electrons are monitored towards the energy storage through the input regulator. Then after the separation of holes and electrons, they are separately allowed to collide at a junction point by moving in the direction opposite to each other and their collision produces spark/current/ power. Then at the end of the process using output regulator this power is supplied to the sensor nodes. This single solar system can produce power from microwatt to megawatt depending upon the size of solar panel. A generalized solar energy harvesting system is shown in Fig. 7. This technique of energy harvesting by using the photovoltaic (PV) effect of converting the light into current using some semiconductor materials, generates the highest energy density as compared to the mechanical and thermal Energy harvesters [36]. Solar energy harvesting technique also known as Photovoltaic energy harvesting technique, is suitable for large systems but its power generation process is strictly dependent on the conditions of environment and the light availability. For energy to be supplied in a continuous manner, during night hours energy is stored in the energy storage or energy buffer. For energy storage Lithium Ion secondary cell is the most commonly used energy storage battery/buffer. It has remarkable storage capacity for energy, very small internal resistance and prolonged lifetime [37]. The most salient element of the solar energy harvesting model is the load by which the harvested energy is utilized and this component consists of I/O regulators, processing units and transceivers. It is also known as a small sensor node. The load's transceiver - that can transmit and receive communications, is basically the most energy utilizing part [38]. Photovoltaic energy conversion mechanism produced higher energy levels as compared to other energy harvesters and is suitable for large energy harvesting systems. Its generated power and efficiency depend upon the light availability and environmental/weather conditions. The type of material used for the photovoltaic cell also effects the system's efficiency and power level. Fleck [39], Enviromote [40], Trio [41], Everlast [42], and Solar Biscuit [43] are the commonly known implementations of the solar energy harvesting sensor nodes. Fig. 7 Solar Energy Harvesting System for WSNs A lot of research work has been done to increase the life time of a wireless sensor network. This work includes the major factor of data size reduction but reducing data size increased the delay time and the waiting time to collect a maximum amount of data for compression. So in [44] the authors mentioned that since solar energy is denser and heat enriched energy so it is more preferred source to harvest energy for WSNs. But the amount of energy harvested using this technique can be in excess that is more than the energy required for a particular operation. Yang et al. proposed a WBAN'sApplications Blood pH measurments ECG Heart Beat Rate Recording Breathing Activity Insulin Pump Motion Sensor Glucose level Blood Pressure EEG etc.
  7. 7. 7 model to determine the amount of excessive energy for a given period of time. M. Kang, S. Jeong, I.Yoon et al. proposed an energy adaptive selective compression scheme (EASCS) which calculates an energy threshold that determines if there is any excessive or surplus energy. If it is not found then the data is compressed to reduce its energy consumption and transferred otherwise it is transferred without compression to reduce delay & waiting time for further data. It prevents the blackout time in which the sensor node stop working without any warning. In [45], Solar Castalia, a Solar Energy Harvesting Wireless Sensor Network Simulator is presented that can surpass various solar energy harvesting sensor systems by configuring the solar panel types and size and the rechargeable batteries. It can also simulate the season/weather when the target wireless sensor node is about to operate. E. EFEH TECHNIQUE Electric-field energy harvesting (EFEH) technique is an emerging technique which act as an alternative for next generation wireless sensor networks. It is a promising technique to stop the wastage of energy, minimize loss and increase operational efficiency. In [46] authors proposed a multi-layer harvesting model and a practical, general use implementation model that support a vast range of network topologies by assigning different voltage levels. In this technique whenever the power is on, the sensing nodes sense the presence of electric field in the overhead power supplies and keeps on storing it in the storage capacitor until the max power level is obtained and the electric power is supplied to the needy sensor node. Experimental results in [46] deduce that EFEH technique is a better solution to build an energy efficient WSN with long life time, more robustness, greater throughput and improved flexibility which lead to the deployment or distribution of large number of sensors. F. MFEH TECHNIQUE Another technique to harvest energy for wireless sensor networks is Magnetic Field Energy Harvesting Technique. In this technique from the electromagnetic field created around the current carrying conductor magnetic field is separated out and by using current transformers electric energy is collected from the magnetic field. Since magnetic field is produced due to alternating current so a max amount of current flow is required in the conductor [46]. S. Yuan el al. in [47] proposed a magnetic field energy harvester which is more efficient and free standing and to lessen the demagnetization factor the path of magnetic flux in helical core can be increased leading to the increased magnetic flux density and hence sufficient amount of power will be produced. G. TEH TECHNIQUE Thermal energy is generated by using either thermoelectric energy harvesting technique or pyroelectric energy harvesting technique [48]. Thermal based energy harvesting technique utilizing thermoelectric generators (TEG) produced electric energy by using heat energy which is then converted to electrical energy by the use of Seebeck effect [49]. The TEG utilizes hot and cold plates with semiconductor thermocouples between them. Upon heating, electrons and holes are separated. Holes are represented by positive signs while electrons by negative signs. A semiconductor material carries carrier electrical charges, electrons (-) and holes (+). Higher the temperature is provided at hot plate, more current will be produced. While the other plate/sink contains lower temperature due to which electrons and holes move towards it having the low level of heat. They move from higher to lower temperature to obtain equilibrium. Hence more the electrons and holes are in number, greater the potential/temperature difference will be created leading to generation of more voltage as shown in Fig. 8. Then the Thermal DC converter produces DC power utilizing these electrons and holes and then after power conditioning energy is supplied to WSNs/Sensor nodes [12], [50]. Fig. 8 Seebeck Effect’s Mechanism Recently with the advancement and development in thermoelectric materials up to 10% energy efficiency is achieved. 0.14 micro-watt/mm2 power density is achieved for a 700mm2 device at the temperature dif. of 5 K. The phenomenon of Thermal energy Harvesting is described visually in Fig. 9. Electric energy can be produced by heating Pyroelectric materials which do not require a continuous temperature difference unlike the one required by thermocouples in TEGs but they require time varying temperature changes. These temperature changes alter the alignment of atoms in material’s crystalline structure which lead to the production of voltage or electricity. The leakage of generated voltage will occur if the continuous temperature change is not applied to the pyroelectric material. With pyroelectric energy harvesting techniques (PEHT) maximum efficiency can be achieved as compared to thermoelectric Harvesting technique (TEHT) because PEHT can harvest energy from high temperature sources while TEHT can harvest higher amount
  8. 8. 8 of energy as compared to PEHT but its efficiency is limited as it is dependent upon the temperature difference ∆T. This dependency is because the TEGs can’t have efficiency η greater than the Carnot Cycle (∆T/Th) which has greatest efficiency and four processes of reversible isothermal gas expansion, adiabatic gas expansion, isothermal gas compression and adiabatic gas compression [51] and is the ratio of temperature difference and the maximum/highest temperature that can be applied [52], [53]. In [54] Hybrid Indoor Ambient Light and Thermal Energy harvesting mechanisms are proposed to extend the lifetime of the WSN's node that using only one power management circuit does the conditioning of output harvested power. Fig. 9 Thermal Energy Harvesting System for WSNs H. FEH TECHNIQUE For addressing power consumption problem using ambient source, the technique is flow based energy harvesting that utilizes rotors and turbines and with their rotational effect electrical energy is produced either by using wind or water. Flow based energy harvesting technique is further subdivided into Wind energy and hydro energy. Thermal and flow energy harvesters are Ambimax, SPWTS TEG [12], [55], Wearable TEG [56], Flex TEG [12], [57], Commercial Hydrogen Crator, VAWT [58], AFII etc. Room Heater TEG are made by heating one side of its thermoelectric module and cooling the other face letting an electric current to be produced and it has long life cycle, simplicity and high reliability and no moving parts [59]. Wind and Hydro energy harvesting is considered as dynamic fluid energy harvesting mechanisms. A Flow energy scenario is shown in Fig. 10. Fig. 10 Flow energy Harvesting Scenario a) WEH Technique Wind energy, like solar energy is also freely available and is affordable. It is a process of converting wind or air flow into the current or electricity. In this process of producing current, a wind turbine of right size is used to harness the actual motion of air to produce electricity. By utilizing this technique alternative energy/power supply will be provided. In this technique gear/motors/generators move the turbines & rotors and rotor’s frequency is then pass on to the FV (frequency-voltage) convertor which as the name suggested converts this frequency into voltage/current which is supplied to the Sensor nodes. To harvest energy from wind or air sources, micro wind turbine systems or micro wind harvesters and electromagnetic wind generators are used [60]. In [60] for the purpose of wind turbine a plastic four bladed horizontal axis wind turbine is used which has a diameter of 6.3cm and length of 7.5cm. A large number of generators are attached to its shaft that let it to harvest a great amount of power even at low speed. The most commonly used method is the conventional wind turbine mechanism for harvesting wind energy but with the increase in size its efficiency reduces due to the increased frictional loss’ effect and the reduced surface area of the blades [27] . In [61], based on the piezoelectric cantilever, a new piezoelectric flow energy harvestor is introduced and also that the piezoelectric devices offer the potential as a flow energy harvester in the absence of the electromagnetic induction. The output power of the micro wind belt generators is very high at the high wind speed but it significantly reduces with the decrease in the wind speed and these generators can be extremely noisy [27] . In [62], a small wind generator for wireless sensor applications consisting of an aerofoil connecting to a cantilever spring is presented. The air force on the aerofoil make the cantilever to bend and when it is bend the air force is reduced so that it can move back to its original shape. This process of applying airflow is repeated multiple times and the movement of the aerofoil produces a change in the magnetic flux and generated electric power. b) Hydro EH Technique In Hydro based technique which utilizes water power and generates energy through the use of Hydro-generators. These hydro-generators produce power around about 18 mili-watts. In Seawater batteries, Microbial Fuel Cell can also be used for underwater energy harvesting mechanism. By using this technique 1200mWh per day can be produced. Furthermore, energy can be obtained from some external sources like mechanical wastes and human based energy. Energy from the mechanical wastes can be harvested using vibration to electricity conversion mechanism. This type of energy harvesting was initially introduced for low power generators. Using three basic mechanisms of electromagnetic, electrostatic and piezoelectric transductions, vibration to electricity conversion is processed. [63].
  9. 9. 9 III. EFFICIENT ENERGY BUFFER ELEMENTS An ideal energy buffer would be the one that can save energy in abundance without being affected by it and can keep it save in energy buffer even when it is not in use. So considering all these factors, energy buffers can be selected out either from rechargeable batteries or from the supercapacitors [52] and their respective best elements are also mentioned. a) Rechargeable batteries Rechargeable batteries use electrochemical cell to store energy. These batteries consist of a cathode, an anode and an electrolyte. There are some important technologies that'll be used in the construction of the rechargeable batteries. Some mostly used ones are: Nickel Cadmium (Ni-Cd), Nickel Metal Hydride (NiMH), Lithium Ion (Li+ ), Lead Acid (Pb Acid), Lithium Iron Phosphate (FeLiO4P) and Lithium Polymer (Li Po). The anode's ability to release negatively charged particles in oxidation reaction and cathode's ability to attract them in reduction reaction will lead to the determination of the voltage being produced from a cell. Due to these abilities the reactions of both the anode and cathode are known as reduction reactions due to the hydrogen electrode and is termed as standard electrode potential or standard reduction potential (E0 ) given by unit of Voltage. Some E0 for commonly used batteries are listed in Table 2. TABLE 2 SOME E0 FOR COMMON BATTERY TECHNOLOGIES Technologies for Batteries Reactions E0 in Volts Year Li [4], [45], [52] Li+ + e-  Li(s) -3.05 2011, 2014, 2015 Ni-Cd[45], [52] 2NiOOH + 2H2O + 2e-  2Ni(OH)2 + 2OH- +0.48 2014, 2015 Ni-Cd[45], [52] Cd(OH)2 + 2e-  Cd + 2OH- -0.82 2014, 2015 Pb Acid[52] -2 4+ SO2PbO - + 2e+ + 4H O2+ H4PbSO +1.70 2014 Pb Acid[52] - + 2e4PbSO -2 4Pb + SO -0.35 1014 b) Supercapacitors A supercapacitor, formerly was known as electric double layer capacitor (EDLC) now sometimes also called as ultra- capacitor, is an electrochemical capacitor with high capacity. It also have very much higher capacitance values as compare to other capacitors which fills up the gap between rechargeable batteries and electrolytic capacitors. The power density of the commercial supercapacitor is ~5Wh/kg while that of Li-ion batteries is above 200Wh/kg. They are of 3 types: double layer capacitors, pseudo- capacitors and hybrid capacitors shown in Fig. 11. Fig. 11 Types of Super capacitor Porous carbon based electrodes produced from burnt coconut shell, are used by the double layer capacitors and are put within the electrolyte and upon applying voltage, charges in the electrolyte will attract to the carbon electrodes. While in pseudo-capacitors, capacitance is produced when the electrolyte’s ions perform reaction with the electrode's atoms and these electrodes are made of metal oxides. Hybrid capacitors are the mixture of both of the previous ones. IV. ENERGY HARVESTERS A sensor node is something that sense something depending upon the program fed in to it. It is also known as a Mote (mostly in North America). It has a sensing subsystem/unit, processing unit/subsystem, a power source and a transceiver unit/ information processing or wireless communication unit. A basic architecture of a general Sensor node is elaborated diagrammatically in Fig. 12. Fig. 12 General Architecture of a Sensor Node An Energy Harvester is also basically a sensory node that sense the presence of its source/input material and utilize it in the process of energy harvesting. A. RF SENSOR NODE/ENERGY HARVESTERS In [64] Dickson's charge pump circuit’s design is presented with a multi resonant loop antenna for Radio Frequency energy harvesting. This circuit enables the RF Harvester to process efficiently at both outdoors and indoors. The proposed energy harvester gains sensitivity of -21.2 dBm and -17.1 dBm at 900 MHz & 2.4 GHz respectively and at power
  10. 10. 10 level of 10MΩ output load at 1V output voltage shows working rate having the efficiency of 25.7%. The authors presented dual band operational processing results of RF harvester by using a single loop antenna whose impedance facilitates simple impedance transformations at both mentioned frequencies resulting in reduced loss in matching networks and they built Dickson charge pump using HSMS- 285C Schottky Diodes due to which manufacturing cost is reduced as compared to integrated ones. This design technique can facilitate the dual frequency band energy harvesting using loop antenna. The Texas Instruments’ (TI) analog experts have discussed multiple RF Sensor Node Development Platforms for 6LoWPAN and 2.4 GHz Applications in [65]. Some of these platforms are CC2520, MSP430F5438A, TMP106 and TPS22901 etc. A dual-path CMOS rectifier with adaptive control for ultra-high frequency (UHF) RF energy harvesters is introduced in [66]. It includes both low power path and high- power path. The dual path rectifier is included in the 65nm CMOS process along with an adaptive circuit. The power convention efficiency can be achieved above 20% with an 11dB input range from -16 to -5 dBm. The sensor nodes sensitivity of -17.7 dBm is achieved with 1V voltage level. Majdi M. Ababneh, Samuel Perez, and Sylvia Thomas in [67] introduced a power management circuit which improves the efficiency of the DC-DC converter by using particle swarm optimization technique in which fitness function generated from the converter's efficiency is used and inductor and on time are selected as optimized parameters. This design technique improves the efficiency level of the power management circuit to 9.25%. This technique can be utilized in portable apps to increase the battery life. RFEF Technique is immensely being popular in green technology because of the excessive deployment of mobile phone base stations, television base stations, Wi-Fi, Bluetooth etc. So to increase the low RF energy obtained from the receiving antenna from AC to DC focusing on low RF input, the authors in [68] presented a 1.8 GHz and 2.4 GHz Multiplier Design for RF Energy Harvester in Wireless Sensor Network. For this purpose Dickson Multipliers are also optimized by using advanced Design System which gives efficiency of 6.5 % at 0.96 V and 5 % at 0.76 V and at 0 dBm for 1.8 GHz and 2.4 GHz respectively. With the introduction of the applications that exploits industrial, civil, and aerospace infrastructure, it is mandatory for sensor nodes to be robust and power efficient especially in locations that are difficult to access. For this purpose, microwave energy is examined for powering wireless sensor nodes that are deployable. Hence a prototype micro strip patch antenna was introduced in [69] to operate in the 2.4 GHz ISM band and to gather directed RF energy for powering up a Wireless device. The power was then used further to charge the sensor node to 3.6V in 27s which was enough to two piezoelectric sensors. Apart from these mentioned sensor nodes and harvesters multiple RF harvesters have been introduced in the past named as ST Microelectronic Modules [70], Texas Instruments eZ430 - RF2500 [71], Powercast’s Powerharvester [17], [72], Ambient Radio Frequency based Harvester nodes and multiple antenna based RF Harvester nodes. B. SEH SENSOR NODE/ENERGY HARVESTERS Using an on-chip solar cell an ultra-compact single chip solar energy harvesting integrated circuit for biomedical implant applications is introduced in [73]. The authors used an on-chip charge pump along with the parallel connected photodiodes which improves the efficiency to 3.5 times as compared to conventional stacked photodiode. In order to improve the area efficiency a photodiode assisted dual startup circuit also used which enhanced the startup speed by 77% and a low startup voltage of 0.25 is obtained by using an auxiliary charge pump with zero threshold voltage devices in parallel with main charge pump. To improve the energy harvesting efficiency they utilized a synthetic charge pump and solar cell area optimization technique. Experimental results show that a maximum efficiency of 67% is achieved by utilizing this harvester. Due to the change of oil prices and growing degree of pollution led to the alternative and renewable energy sources that are less oil consuming and free of factors that enhances pollution. Hence the advancement of technology led to the usage of photovoltaic systems which are pollutant free and non-oil consuming and usage of converters in these systems enhances the efficiency rates and reduces cost. In [74] a photovoltaic system with maximum power point tracking facility is introduced. Generally maximum power point tracking control is very challenging due to the conditions that calculates the quantity of sun energy and transfer it into the photovoltaic generator. The power generated by the solar energy harvester in [74] that utilize photovoltaic generator, is maximized by using sliding mode controller that handles the boost converter connected between the photovoltaic generator and the load. After designing and modeling this system is tested under MATLAB/SIMULINK environments. For this processing the SMC-MPPT algorithm is divided into two steps. In first step the actual reference voltage level at which the maximum power level is achieved, is calculated while in the second step the SMC PVG voltage regularization is done at the reference voltage. The stability of the proposed SMC MPPT system is analyzed and verified using the Lyapunov theory. The MPPT algorithm ensures the robustness and high tracking performance rates.An advanced form of technology is WSN using which one can monitor environmental or physical conditions such as light intensity, temperature, pressure etc. Sensor nodes in a wireless network are generally powered by two AA size batteries which have limited life time and needed to be replaced whenever they expired. Hence this energy harvesting system of solar power is introduced along with other solutions. A simple and low cost energy harvester is developed and introduced in [75]. Due to the cheap, maximum and natural availability and high power density of solar power in the
  11. 11. 11 environment, sunlight energy is selected as an energy harvesting source. Though solar energy have some drawbacks that it is available only in daytime and is dependent upon the sunlight density but still it is much better and cheaper as compared to others. The authors in [75] proposed an energy harvester that contains 4 major components of solar panel, batteries, output regulators and wireless sensor network node/mote. While selecting the type of solar panel several factors of open circuit voltage, short circuit current, maximum power point (MPP) and the IV characteristic curve need to be considered and for building up this harvester a MSX-005F solar panel is considered which has maximum power of 0.5W. Due to the seasonal cycle availability of the sunlight energy an energy buffer/storage is required to provide power un-interrupted. Hence three types of batteries of lithium-ion, nickel cadmium and nickel metal hydride are considered but later the lithium ion battery is discarded due to its long lifespan and low discharge rate, expensiveness and due to the fast discharge rate of nickel cadmium battery, it is also discarded and Nickel metal hydride (NiMH) battery is selected due to its higher energy density, lower life cycle and efficient rates of energy charging and discharging. An output voltage regulator was needed to boost up the voltage supplied by the battery to the desired voltage level. Hence for this purpose a DC-DC boost converter was used and the used model is MAX1724EZK33 from Maxim Integrated because it requires a minimum number of external components. Since two NiMH batteries are used having a capacity of 1500mAh and a voltage supply of 2.5V so energy supplied by the battery will be B = 1500 mA × 60 × 60 x 2.5V = 13500 J And the duration of the battery power supply to sensor node would be Tb= B/E = 13500/7897.82 = 1.7 days The average harvested energy produced by the solar panel is 12231 Joules within the time span of 1.1 days. Therefore from experiments it can be concluded that solar panel requires only 1 day to be fully charged while batteries can power nodes for 1.7 days. In [76] an efficient solar energy harvesting single axis sun tracking system with dynamic offset parabolic mirrored reflector dish to enhance the efficiency of solar energy harvesting system is introduced and its performance compared with static solar panel and solar panel with static mirrored reflector system is better. It can harvest more energy as compared to others. The parabolic mirrored reflector dish can reflect radiations of light and can harvest energy efficiently by focusing the reflected light at its focal point where solar panel is placed. For rotation of dish in the direction of sun's motion, clock tracking system has been used and an Arduino UNO controller has been used for dish's rotation by an angle of 6.25 degree at 30 minutes periodic interval during 6am to 6pm. This harvester can generate average output voltage of 7.822 volts and 6.144 mA and is capable of showing 81% more efficiency rates as compared to static solar panels and 48.26 % more efficient than solar panel with static reflector system. This harvester autonomously operate the motor driven dish by harnessing a portion of harvested solar energy which is stored in rechargeable lead acid battery. Moreover different harvesters of solar energy for WSNs are IRN [77], BLSH [78], MSIL [79], LTSN [80], Hydro Watch [81] and Heliomote [82] etc. C. TEH SENSOR NODE/ENERGY HARVESTERS In [83] a cheaper source to harvest thermal energy than thermoelectric generator is provided by the Electrochemical thermocells which by utilizing the temperature dependence of electrode potential, produces electrical energy and redox mediators for transmission of charge in the electrolyte. The electrolyte in these thermocells acts like semiconductors in conventional thermoelectric generators if the charge transfer resistance and the thermal and ionic transport occur by thermal convection of the electrolyte. In [84] B. Gusarova, E. Gusarovac, B. Viala et al. proposed a unique thermal energy harvester. This harvester does coupling of both pyroelectric and piezo- electric effects of polyvinylidene fluoride (PVDF) with shape memory effect of TiNiCu alloy. To harvest, the small and quasi-static temperature changes and the superior flexibility of the polyvinylidene fluoride is combined with the great temperature induced strain of the shape memory alloy and the harvester of a size of post stamp obtained 0.41 mJ/cm3 per event of temperature variation of 20◦C energy density. At 70◦C along with 4 polyvinylidene fluorides the harvester can immediately charge the sensor node without storing any energy in the storage unit. An electret based unsteady Thermal Energy Harvester using Potassium Tantalite Niobate Crystals is presented by H. Xie et al. in [85]. This harvester is composed of three parts: external load, electret acting as a permanent voltage source and temperature sensitive dielectric capacitor. As ambient temperature the permittivity of dielectric changes varies, producing the change in the amount of the induced charges which led to the production of external current by fluctuating temperature. Global environmental challenges and energy crises has led to the utilization of the ambient energy. A lot of chemical reactions that are frequently being used/ processed in industries and laboratories lead to the production of large amount of un-needy heat, almost every 2 hours. For example combustible reactions of natural gas and coal, different methods of waste water treatment in industries etc. produces great quantity of heat which has temperature below 1300 C. This heat can be recycled to produce electric power. Many methodologies has been proposed for this purpose including stirling engines which can convert thermal energy into electrical energy [86] Organic Rankine cycles use refrigerants and hydrocarbons to harvest heat up to 200– 3000 C [87] but due to the small Carnot efficiencies these techniques are not suitable for the low grade heat. In paper [88] a pyroelectric device/harvester is presented that utilizes carbon nanotube(CNT)/PVDF/CNT sandwich as a potential approach for harvesting heat from chemical process. For this
  12. 12. 12 purpose pyroelectric device is attached to the outer side of the beaker having various chemical exothermic reactions. This way heat is converted to electricity and an output voltage 9.1 V with impedance of 100MOhm and short circuit current 95 nA is noticed when the reaction of sodium hydroxide and hydrochloric acid occurs in the beaker. Energy harvesting is the most demanding technology/methodology to power up any sensor node or rechargeable things. In [89] an approach to harvest human body heat for powering wearable devices is presented and this work focused on the optimization process of power conversion efficiency from human body to the application. Using this approach the micro TEG produces up to 65% higher output power per area in a laboratory testbed and 1– 15% in a real world experiment on the human body depending on physical activity and environmental conditions. Furthermore SPWTS TEG [12], [55], Wearable TEG [56], Flex TEG [12], [57] are some TEG based thermal energy harvesters. D. MDEH SENSOR NODE/ENERGY HARVESTERS Since mechanical energy is basically obtained from vibrational effect, piezoelectric effect etc. So some of its energy harvesters are mentioned below. In [29] using multiple nonlinear techniques a piezoelectric vibration energy harvester is presented. Vibrational energy is available in our surroundings in abundance like from different types of industrial & commercial machines, vehicles, railway structures etc. The ideology of vibration to electric energy production was proposed by Williams and Yates in 1996. Since then it is an attractive technique of producing energy and powering low power devices. In this technique the shape of the piezoelectric material or cantilever is changed to nonlinear form to generate energy from varying vibrational frequency and the bandwidth is broaden. The multiple nonlinear effects can be achieved in this device including Duffing-spring effect, impact effect, pre- load effect, and air elastic effect. Dedicated sensor nodes are frequently being used in everyday life aspects of security, tracking, monitoring and measuring performance metrics etc. In [90] the authors presented an electromagnetic vibrational energy harvester to enable sensor nodes to power themselves up. This harvester is basically a unique conception of the electromagnetic, proof mass based energy harvester which tends to enhance the vibrational velocity of any vibrating body twice. Due to the large power capacity and reliability an electromagnetic design is selected for this harvester. As the electromagnetic generator's output voltage is directly proportional to the squared relative velocity between the magnets and the coils and the squared magnetic field strength through the coils. To amplify the velocity of the magnet and coil, a unique frame of spring steel compliant mechanism was utilized. The vibrations from the planted machinery induced proof mass and the shape of the frame enhances the relative motion between magnets and coils of the electromagnetic energy harvester. At normal frequency operation, the harvester shown up to 0.91V AC open voltage and a max power of 2mW. Vibrational energy harvesting is actually a phenomenon of converting mechanical energy from ambient sources to the electrical energy to supply power to remote sensor nodes. This harvesting mechanism work well as compared to the linear resonator that works very poorly at a farther distance from their natural frequency source while nonlinear energy harvesters work much better because they utilize vibrational effect over a wide range of spectrum. Hence the authors in [91] presented a hybrid non-linear energy harvester that merges the bi-stability with internal resonance to increase the frequency bandwidth. The presented harvester contains a piezoelectric cantilever beam, the output voltage and the movable magnet. Nonlinear vibration energy harvesting with internal resonance contains a spring and a movable magnet with a piezoelectric beam inside the two of them and a fixed magnet. The beam is displaced in sideways to produce voltage. The larger the displacement, the larger the piezoelectric output voltage. The numerical techniques of Runge Kutta Method of long time integration and the shooting methodology were utilized for the verification of the analytical results. A feasible study of impact based piezoelectric road energy harvester for WSNs in smart highways is presented in [92]. The main goal of this study is to design and examine the impact based piezoelectric road energy harvesters as energy sources for different sensor nodes and smart highways. The harvester discussed in this research work is much better than the existing ones. The output power of this harvester is first measured using a machine known as Universal testing machine that does the application of the axial load with a controlled loading frequency then a mobile loading simulator simulate the real world traffic load on a lab scale. At the end the result of the maximum output power of mentioned energy harvester is achieved which is 483 mW and 21.47 W/m2 . Hence a basic piezoelectric road energy harvester is build up that can be used for powering up the WSN's sensor nodes. AEM MEEG [93], Piezoelectric MEEG and micro Piezoelectric MEEG [94] are also the electric energy harvesters/generators of Mechanical energy harvesting mechanism. E. HEH SENSOR NODE/ENERGY HARVESTERS Human energy harvesting sensor nodes can be powered up by utilizing the energy harvested from the human walking motion. The continuous development in the wearable energy harvesting technology has led to the discovery or introduction of the more advanced devices that deliver increased power outputs which can be used to provide un-interrupted energy supply to body sensors to get the energy autonomous WSNs. In [95] a wearable energy harvesting powered wireless sensing system is introduced which contains 4 parts of a magnetically plucked wearable knee-joint energy harvester (Mag-WKEH) to harvest energy from knee-joint motions during human walking motion, a power management module (PMM) with a maximum power point tracking (MPPT)
  13. 13. 13 function, an energy aware interface (EAI) in order to deal with the dissimilarity between the energy generated and energy required and the fourth one is an energy aware wireless sensor node (WSN) for data sensing and data transmission. Experimental test bed on the human beings walking on the treadmill while wearing this proposed system at different speed levels, showed that the energy power output of Mag-WKEH with the increase in the walking motion from 3 - 7 km per hour, increased from 1.9 ± 0.12 to 4.5 ± 0.35 mW. This out energy/power supply was sufficient for WSNs and within the active time period of 2.0 ± 0.1s they can do their processing in duty cycle from 6.6 ± 0.36% to 13 ± 0.5%. M. Geisler, S. Boisseau, M. Perez et al. in [96] introduced a technique for the optimization of electromagnetic energy harvester and converting the low frequency of the body motion in to the usable power supply and use it to power up the WBAN's sensor nodes. This methodology for the targeted human being's running activity, optimizes the nonlinear inertial energy harvester and an electrical power supply of 4.95mW in a resistive load and 3mW in a 2.4V NiMH rechargeable battery is produced. A Wireless power transfer system for a human motion energy harvester is presented in [97] by P. Pillatsch et al. They presented a methodology to actuate a rotor wirelessly in the rotational piezoelectric energy harvester by utilizing a magnetic circuit's reluctance coupling property. This coupling is done with the external running rotor which has multiple magnet stacks permanently attached to it. This phenomenon led to the possibility of recharging a battery or super capacitor even in the absence of human motion. F. FEH SENSOR NODE/ENERGY HARVESTERS FEH Sensor Node/Energy Harvesters are further categorized to WEH and Hydro EH Sensor nodes/Energy Harvesters a) WEH Sensor Node/Energy Harvester WSN is now becoming more and more advanced technology from which we can say that in near future everything we use will be internet connected. But in spite of WSN's thousands of advantages they are suffering from energy consumption issue due to which energy harvesting mechanisms are introduced. In [98] a wind energy harvester for autonomous WSNs is presented which will improve the prediction of weather/wind conditions. In this work the wind is exploited as an environmental energy source and uses a small wind turbine. The weather forecast is also used along with the actual wind state and at the end the correct predicted value is selected on the basis of the error between the real wind state and the previously predicted value. For experimental analysis a Powwow platform connected with wind turbine and rotation per minute circuit is used and different wind conditions are created by using three different fans at different distances from the harvester and the configuration is maintained for ten minutes. The node sends the rotation per minute value to the receiver during the process after every minute and this value is compared with ten different values and at the end average speed is determined. Then the noted or selected rpm value is converted to harvested energy. In [99] a wideband topology and a design optimization technique is presented for piezoelectric wind energy harvester to maximize the wind energy, Hence the obtained maximum power density, maximum efficiency, and cut-in wind speed of the harvester are 0.59 mW/cm3, 24%, and 2.1 m/s, respectively. Instead of WSNs wind energy harvesters are also used for autonomous embedded systems [100] and can be deployed as building skin based on zinc oxide [101]. b) Hydro EH Sensor Node/Energy Harvester With the passage of time and the advancement of technology especially wireless technology, energy harvesting techniques are becoming the alternative of the conventional batteries. For energy harvesting process humans have already used the technology in the form of the windmill, watermill, solar energy and geothermal energy etc. These harvesting mechanisms provide power level of [102] kW or MW and the energy harvesting process is limited to micro energy harvesting. Piezoelectric material can be used for small devices. This material has a capability of converting the dynamic pressure into required electric energy hence the dunamic pressure or load can be human motion, water, wind, tides, rainfall etc. The proposed system model in [98] contains a water tank, set of nozzle to increase the velocity factor of the fluid, pipe to circulate the water flow. This model can be used at location swhere maximum water supply is available such as river etc. If the existing water is not enough then the water can be stored in the reservoir tank and water can be circulated using the pump and recirculation of water can be done using the electric motor. For the transportation of any type of resources underwater pipelines are mandatory and it is also important to do automatic monitoring of pipelines using WSNs and for longer lifespan of WSNs continuous energy supply is required. So for this purpose a methodology for near optimal piezoelectric energy harvester design is presented in [103] to enable the wireless sensor node self-powered for in pipe monitoring by utilizing kinetic energy of water flow. The Turkish Cyprus water pipeline project tis considered for experimental purposes and the designed energy harvester can produce energy between 820microWatt to 12.3 mW, with an average velocity of 1.4m/s and with a negligible head loss of 1.5mm. More Flow based energy harvesters are Ambimax, Commercial Hydrogen Crator, VAWT [58], AFII etc. Since EFEH technique and MFEH technique are so novel and are still under research so their energy harvesters or sensor node have not yet been surveyed or researched out. V. OPEN RESEARCH CHALLENGES Some research challenges that have not been addressed yet are: A. GENERALIZATION OF HARVESTERS One of the research challenges of the WSN’s energy
  14. 14. 14 harvesting scenario is to harvest as many energy as possible from multiple sources. So this requirement leads to the implementation and deployment of a generic harvester that can be used to harvest energy from multiple sources. B. FAULT TOLERANT WSN Another key challenge of the WSN’s energy harvesting scenario is to make the WSNs fault tolerance so that they can keep on generating energy and supply continuous power to the needy sensor node. So building a WSN that can’t be effected by the failure of any energy buffer will lead to the continuous power supply mechanism. A WSN must not be affected by the failure of any node or anything connected to the WSN. This is a reliability concern. Fault tolerance is the ability to maintain the functionalities of network without any interruption even if any node fails or energy buffer failure. C. EFFICIENT COMMUNICATION SYSTEMS AND SENSORS For a WSN to be working more efficiently and for the betterment of the energy consumption process it is necessary to work on the development of low power and low cost communication systems and sensors so that WSNs can perform much better. D. BETTER RECEPTION OF SIGNALS Another key challenge is to improve the mechanism of receiving signals because if a node remain busy in getting a distorted signal much energy will be lost/consume so there is a need to introduce different methods to bring improvement in the reception of signal so that less energy can be consumed and process can be fasten up. VI. DISCUSSION From the wireless sensor network’s point of view and by keeping in mind the detailed elaboration of the Energy Harvesting techniques, it can be pointed out that RF based energy harvesting technique is very promising and the solar energy harvesting technique and thermal energy harvesting techniques by utilizing the photovoltaic cell and thermoelectric generators respectively will also work very effectively because the energy sources in both the techniques are available in abundance and very cheaply. But in case of flow based energy harvesting mechanisms like wind and hydro, no doubt have their own capabilities but are not a source of maximum and continuous power generation and are little expensive as compared to others because in order to run turbines or rotors continuously, additional power supply is required. While for mechanical and human based energy harvesting, the resources to generate energy like oil, gas, coal, nuclear power plants etc., are limited and expensive since they do not exist in abundance. The description about energy harvesters is summarized in Table 3. V. CONCLUSION WSNs have now become very attractive in lots of fields of technologies and are attracting many stakeholders and it seemed that they are suffering from energy consumption issues but in this work lots of energy harvesting techniques to overcome the issue of energy consumption factor have been surveyed out. These techniques will gradually advance towards the implementation and deployment level, from which it is concluded that in near future WSNs can completely overcome the ragging issue of energy consumption. Then some appropriate storage elements for different techniques that support storage of harvested energy, are also surveyed out. I found out that in this domain of WSNs the current state of art in the modeling of appropriate technique is still immature and is mostly at research level. Lastly some open research challenges that have not been addressed yet, need to take into consideration in near future. VI. FUTURE WORK It is obvious that gradually there'll be a situation when no energy will be left to harvest. Considering the solar energy, this problem will occur during night time. This problem can be minimized by utilizing an energy storage/buffer that can provide continuous power supply even when there is no energy left in the environment, to harvest. Using the elements mentioned in the section III such an energy buffer can be made. In the future the basic focus will be upon the development of autonomously self-charging energy buffers without using any sort of harvesting system and in near future all these techniques will be on implementation level. Furthermore a generalized harvester to implement any of these mentioned techniques on a single harvester will be deployed and future concerns will be related to the development of fault tolerance WSNs along with the betterment in the reception of signals and efficient communication systems and sensors as well. TABLE 3 SUMMARY Harvesters Probable Power Produced per Area or Energy density Efficiency Rate Pros Cons Solar Energy Harvester [22], [36]–[38], [45], [58] 15 mW/cm3 Around about 40% [52] Limit-less energy in daytime Fragmentary supply Thermo-electric Harvester Depends upon the 10 to 15 % Continuous power supply can be Very High temperature is required
  15. 15. 15 [12], [48]–[50], [53]–[57], [59] temperature difference and most commonly 40 µW/cm3 [52] possible Radio Frequency Based Energy Harvester [17]– [19], [21], [104]–[106] Depends upon frequency being used, approximately about 50 nW/cm2 Above 70% [52] Continuous power supply can be possible Abrupt Decrement in power in case of greater distance from transmitter Mechanical Energy Harvester [12], [25], [26], [27], [52] 330 µW/cm2 nil Mechanical power makes a direct, immediate impact wherever it will be used and generation of this energy is quick also. Sending mechanical power over long distances is inefficient because friction in ropes, gears and other mechanisms turn much of the useful mechanical energy into heat before it reaches its destination. Flow Based Energy Harvester WEH [12], [58], [107] 10.4 mW/cm3 About 30 to 40 % [12], [58], The production of wind energy is “clean”. Unlike using coal or oil, creating energy from the wind doesn’t pollute the air or require any destructive chemicals. Wind is free. In the event that you live in a geological area that gets a lot of wind, it is ready and waiting. As a renewable asset, wind can never be drained like other regular, non- renewable assets [107]. Wind doesn’t generally blow reliably, and the wind turbines usually work at about 30% wind capacity or more. If the weather is not favorable then the energy can’t be produced. The wings of wind turbines can be unsafe to natural life, especially birds and other flying creatures which is a threat to wildlife [107]. Hydro EH [26], [27], [36], [108], [109] 0.35 mL at 3.43 m/s speed produces 30.67 µW/cm2 nil Water is a freely available energy source. Another pro of the Hydro Energy Harvesting is that additional power plants can be added to the existing dams instead of building bigger or additional dam sites, whenever needed. Hydro energy harvesters do not pollute the air, water or land like other power plants do. Hydro energy harvesters do not lead to global warming or acid rain [108]. Dams can break and cause havoc with flooding, endangering human and animal life. The building of dams can change flow of water or rivers causing short of water to neighborhood and sometimes leading to the cutting off, of the water supply to local areas. Also that the construction costs are huge and the energy production is mostly dependent on rainfall and can be effected by drought [108]. Human Based Energy Harvesting [63] 1.2 µW/cm2 nil Easy to harvest and can be implemented in multiple places within a single body. Also very useful for health care. Very costly and maintenance is also very costly Electric-Field Energy Harvesting Technique [46] nil max No need for current conversion, available most of the time and easy to implement Unwanted side effects such as burning of power plants or transformers Magnetic Field Energy Harvesting Technique [46] 150 µW/cm3 nil easy to implement, non-complex structure Requires high current flow, safety vulnerability ACKNOWLEDGEMENT I, Farwa Abdul Hannan, after Allah Almighty, would like to express my profound gratitude to my teacher Dr. Rana Asif Rehman for his exemplary guidance, monitoring and constant encouragement throughout this research. I am highly thankful to him for providing necessary information and material regarding this research project and for making it possible. I would like to express my gratitude to my parents also for their support and encouragement which helped me in the completion of this research work. REFERENCES [1] L. University, An Introduction to MEMS (Micro- electromechanical Systems), no. January. 2002. [2] J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Comput. Networks, vol. 52, no. 12, pp. 2292–2330, 2008. [3] A. Ali, A. Khelil, F. K. Shaikh, and N. Suri, “Efficient predictive monitoring of wireless sensor networks,” Int. J. Auton. Adapt. Commun. Syst., vol. 5, no. 3, pp. 233–254, 2012. [4] K. Maraiya, K. Kant, and N. Gupta, “Application based Study on Wireless Sensor Network,” Int. J. Comput. Appl., vol. 21, no. 8, pp. 9–15, 2011. [5] M. Castillo-Effer, D. H. Quintela, W. Moreno, R. Jordan, and W.
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