Revista Ingenio
Ocaña, Norte de Santander-Colombia
No. 1
Enero-Diciembre 2022
ISSN 2389-864X

Review of entrepreneurship in the COVID-19 era

Ph.D Jacob Raglend* A** B*** C**** D***** E****** F

Date received: 23 of june 2021 - Date approved: 30 of november 2021

How to cite:
R. Jacob, B. Ghanishtha, J. Swaminathan, W. H. Vincent, E. Belwin, R. Sitharthan “A contemporary outlook on wireless sensor networks for solar power harvesting” , Revista Ingenio, 19(1), pp.16-21, 2022


While solar energy has been an emerging source of renewable energy for many years now with various studies delving into building more robust and compact solar cells, their use as a power source for mobile and small machinery such as Wireless Sensor Networks (WSN) is less discussed. However, with increasing global efforts in subsidizing more sustainable technology and energy, many studies have emerged in the past decade on building solar power based wireless sensor networks.The combination of novel harvesting circuits, mechanisms to obtain maximum possible power, smart power management algorithms and improving energy technology has provided the necessary framework for self-powered WSN nodes that have much longer lifetime.This paper reviews the newer proposed technology that aids the development of Solar Energy Harvesting Wireless Sensor Networks.

Keywords:Embedded Systems, Internet of Things, Renewable Energy, Solar Power Harvesting, Wireless Sensor Networks

Perspectiva actual de las redes de sensores inalámbricos para la captación de energía solar


Aunque la energía solar es una fuente emergente de energía renovable desde hace muchos años, con varios estudios que profundizan en la construcción de células solares más robustas y compactas, su uso como fuente de energía para maquinaria móvil y pequeña, como las redes de sensores inalámbricos (WSN), es menos discutido. Sin embargo, con el aumento de los esfuerzos mundiales para subvencionar tecnologías y energías más sostenibles, en la última década han surgido muchos estudios sobre la construcción de redes de sensores inalámbricas basadas en la energía solar. La combinación de novedosos circuitos de recolección, mecanismos para obtener la máxima potencia posible, algoritmos inteligentes de gestión de la energía y la mejora de la tecnología energética ha proporcionado el marco necesario para que los nodos de las WSN se autoalimenten y tengan una vida útil mucho más larga. En este artículo se revisa la nueva tecnología propuesta que ayuda al desarrollo de las redes de sensores inalámbricos con captación de energía solar.

Palabras clave:Sistemas embebidos,Internet de las cosas,energías renovables, captación de energía solar,redes de sensores inalámbricos.

1. Introduction
A recent emerging technology,wireless sensor network (WSN) is the backbone of many advances in the Internet of Things (IoT).The applications of these networks have ranged from disaster management,ecological studies,medical monitoring systems,and air quality metrics [2]. One of the major functions of WSNs currently is environmental monitoring which is characterized by its function to transmit data over a large area wirelessly to the gateway node.Amongst the notable standards for wireless sensor networks commonly researchers cite ZigBee,Z-wave,WiFi, and Bluetooth [2-3.The novel and inviting features of WSNs are their reliability which gives the system a large operational lifetime,especially when flexible architectures such as wireless mesh are utilized.At the heart of the performance of any WSN are the wireless sensor nodes and their specifications.

At their core, ever wireless sensor node is characterized by its size, stand-alone power supply, its transmission latency and its sensory accuracy. Over the recent years,sensors have become increasingly accurate at miniscule sizes,therefore it can be deduced that the primary bottleneck in the size of a wireless sensor node is its powering mechanism or the size of the battery.It is observed that a significant correlation exists between the useful life of the individual nodes and their duty cycle as well as the volume of data flow within the system.While there are IoT objects that use high power per unit time, these tend to be less sustainable,therefore it is a standard practice to maintain a design constraint of being powered by a readily available source such as 1.5V IEC 60086 size R6 batteries [2].Though WSNs are mainly low power systems that do not need large batteries,Inherently the use of batteries applies a limit on the operational time of the network after which the system will have to be taken out of service to recharge or replace the batteries.This process interrupts the operation where the wireless sensor is being used and in cases where the network is spread over several kilometers the replacement can be time intensive and impractical.Therefore, a source of energy is needed that provides energy at the place of operation itself without the need for interrupting service,human intervention, or connection to grid. Some such viable technologies are stated in the Table 1.

Source:[1] and [4]

From Table 1 it can be noted that solar power demonstrates the optimal trade-off between efficiency and power density amongst other comparable sources of energy.Furthermore,it should be noted that the size of harvesters of solar energy are becoming smaller by the day,recent cells using nanotechnology have been manufactured in the order of nanometers.The growing market for solar panel manufacturers also provides ample investment and resources for its integration with WSNs.Maurya et al.have stated that near about 15 mW/cm3 of photovoltaic power can be harvested from solar energy for wireless sensors[2].Converters are used to transform this energy to the DC that drives the internal circuitry of the WSNs. Additionally,advancements in storage technology allows the system to function in conditions that are not favorable for harvesting solar energy.The advantages of solar energy that make them optimal for powering WSN nodes, which are given as follows [1]:

• From a theoretical perspective the output from harvesting solar energy is inexhaustible.
• Solar power tends to show a superior power density than other quotidian renewable energy resources.
• Apart from the production of the solar cells,the pollution and carbon footprint of solar energy is null.
• Solar energy shows compatibility with a most devices having diverse ranges rated power characteristics.
• Photovoltaic harvesters are silent,more durable,and less location restricted than other harvesters.

The major objective of this critical review is to extensively encompass the features of a Solar Energy Harvesting based Wireless Sensor Node,to illustrate the known and potential shortcomings faced by such systems,and review in detail the solutions proposed in various recent studies to improve this technology or extend its application.The remaining portion of this paper is organized as follows:Section II aids in a more comprehensive overview of Solar Energy Harvesting Wireless Sensor Networks and provides an outline of the components involved in such a system.Section III provides the problem description or major considerations in designing an optimal system.Section IV reviews literature which proposes new technology to optimize the designs with respect to the considerations in the previous section.Section V provides some simulation platforms developed to aid in analyzing performance of the Photovoltaic Harvester.Section VI gives the overall summary of the review along with the author’s insight into the most efficient technologies in every domain.

2. Major components of solar energy harvesting wireless sensor network
a. Photovoltaic Harvester Subsystem
- Photovoltaic panel/ Solar cell.
- DC Boost Converter.
- Mechanism for Maximum Power Point Tracking (MPPT).
- Addition Intelligent Mechanism for Energy Forecasting.
- Storage Media.
b. Sensory Array
- Sensor Development/Interface Board (SENSOR-PUCK, FLORA, Thunderboard Sense).
- Analog to Digital Converter.
c. Computing and Processing Unit
- Central Microcontroller Device (TI MSP430F1232, STM32F103, Atmel ATmega328).
- Analog to Digital Converter.
d. Communication Unit
- Transceiver Module (Zigbee, LoRa, etc).

The sensor unit performs as the central instrumentation platform which detects physical quantities like temperature,light, humidity,or pressure, see Figure 1.The computational unit then processes this data to useful markers that would provide the system with decision making feedback.As per the mesh architecture these data packets of useful information are relayed to nearby nodes until it reaches the central database or gateway node.The end user can then access this information or it can be used to autonomously drive a control system.The energy harvesting unit, which is a unique feature of this build of WSNs,supply stable power at the operating voltage (3V) to the WSN node to allow continuous supply of energy and uninterrupted service.

3. Modern Wireless sensor mechanisms for solar power harvesting
The following section covers the literature survey related to the key aspects of Solar Energy Harvesting Wireless Sensor Networks where the key obstacles lie and can lead to gross optimization improvements in existing systems.
a. Storage Technologies for Wireless Sensors
Solar energy can be continuously collected and utilized directly by the WSN node,which is known as battery-less operation.This reduces the cost of the solar energy harvesting WSN as well as battery related maintenance.However,it creates contingency issues as power through the sun may become erratic or insufficient in certain environmental conditions.Recent advancements in high efficiency storage devices have promoted supercapacitors to the primary media for SEH storage, whereas traditional batteries are now often only integrated in these systems as a contingency [1].various media for energy storage in solar energy harvesting wireless sensor node have been summarized from various studies in Table 2.

b. Maximum Power Point Tracking
Maximum power point tracking (MPPT) has often been availed in solar energy harvesting in order to ensure the maximum amount of power that can be harnessed through the solar panels may be collected.The maximum power point refers to the to the constant voltage level that provides peak power levels being produced in the photovoltaic cell.In most new designs of solar power systems and charge controllers,some version of the MPPT technique is employed.At its core, MPPT technique aims to make the solar module’s resistance equal to that of the load of the circuit or the battery. Generally, MPPT can boost energy generation by 20%–30% [9-[13].All MPPT algorithms fall into the following wide classifications:
- Perturbation and observation (P&O):
This method alters the operational parameters directly to try to achieve the MPP.This algorithm can be very complex and has been modelled to have optimal performance in various studies but essentially it boils down to the sequence shown in Figure 2a.
- Incremental conductance:This algorithm has been visualized in Figure 2b.Essentially it operates by comparing the incremental conductance of solar energy harvester to the instantaneous conductance.Depending on the feedback, which is either a positive or a negative value,it varies the voltage until a stopping condition (MPP) is reached. Unlike the first method once the stopping condition is met there are no further alterations in the voltage.

Figure 2. MPPT Techniques a)Perturbation and Observation.Fuente.[9] b)Incremental Conductance.Fuente.[9] c)Fractional Open-Circuit Voltage.Fuente.[10]

c. Solar Tracking for Wireless Sensors
As mentioned in the earlier sections of this paper,the main constraint with respect to WSN nodes is their size.Therefore,until recent times tracking,which is common in many commercial PV systems,was not used as the energy used by the tracker would be more than the energy harvested by the system overall.This would put the design into an energy debt and therefore was mostly deemed infeasible.However,many studies in recent literature have proposed trackers that ensures minimal energy is lost with low power consumption which are ideal for WSN nodes.Some of these studies are highlighted in Table 4.


4. Overall summary with highlights of best noted technologies in every domain
Finally,the Table 7 summarizes the domains of literature studied as part of this survey on solar energy harvesting for wireless sensor nodes.Overall,the main features that have led to development in more efficient,long-lasting and compact solar energy harvesting nodes have been storage technologies,maximum power point tracking, solar tracking,intelligent algorithms and developed simulation platforms.The table summarizing this information also provides a critical evaluation of the most optimal and novel technology that has been studied in literature (as per analysis by the author).The reasoning as to why this particular technology has been chosen is also provided.

5. Conclusion
Solar Energy harvesting continues to make its way into the market as the energy resource of the new age. The use of solar power for niche applications such as for powering WSN nodes, proves its versatility as a power source even for smaller machines. This survey provides the following contributions.The fundamental concepts and components of a Solar Energy Harvesting based WSN system have been detailed.This is followed by a review of the challenges and design considerations that are currently experienced in building such systems.Finally, efforts at tackling these challenges made in recent notable literature have been reviewed comprehensively.The future scope of Solar Energy Harvesting based WSN systems is very promising in the field of smart homes,smart cities, ecological monitoring, process control and automation in industries,and IoT applications.This survey is aimed at serving as a reference for future engineers,researchers,and scientists while designing and manufacturing improved Solar Energy Harvesting based WSNs.

6. References

[1] Himanshu Sharma,Ahteshamul Haque,and Zainul A.Jaffery,“Solar energy harvesting wireless sensor network nodes:A survey”, Journal of Renewable and Sustainable Energy,Vol.10,(2),2018.

[2] Charan, Piyush & Siddiqui, Mohd & Mittal, Nupur & Khan, Zohaib.“Solar Power Scavenging for Wireless Sensor Networks.”Journal of Mobile Computing, Communications & Mobile Networks.Vol.3 (3).33-41,2016.

[3] Luo, Yu & Pu,Lina & Wang,Guodong & Zhao,Yanixao.“RF Energy Harvesting Wireless Communications:RF Environment,Device Hardware and Practical Issues.” Sensors. Vol.19,(13),2019.Doi:

[4] J.J.Estrada-López,A.A.Castillo-Atoche and E.Sanchez-Sinencio,“Design and Fabrication of a 3-D Printed Concentrating Solar Thermoelectric Generator for Energy Harvesting Based Wireless Sensor Nodes,” in IEEE Sensors Letters, vol. 3,(11), pp.1-4, Nov.2019,Art no.5500904,Doi:

[5] L.J. Chien,M. Drieberg,P. Sebastian and L. H. Hiung,“A simple solar energy harvester for wireless sensor networks,” 2016 6th International Conference on Intelligent and Advanced Systems (ICIAS),Kuala Lumpur,2016, pp. 1-6, Doi:

[6] K. Kaushik,D.Mishra and S.De,“Stochastic solar harvesting characterisation for sustainable sensor node operation,”in IET Wireless Sensor Systems, vol.9, (4),pp. 208-217,2019,Doi:

[7] Ibrahim, Rosdiazli & Chung, Tran & Hassan,Sabo & Bingi,Kishore & Salahuddin, Siti.“Solar Energy Harvester for Industrial Wireless Sensor Nodes.”Procedia Computer Science.Vol.105,pp.111-118,2017. Doi:

[8] J.J.Estrada-López,A.A. Castillo-Atoche and E. Sanchez-Sinencio,“Design and Fabrication of a 3-D Printed Concentrating Solar Thermoelectric Generator for Energy Harvesting Based Wireless Sensor Nodes,” in IEEE Sensors Letters, vol. 3, (11), pp.1-4, Nov.2019, Art no.5500904,Doi:

[9] P. Mekikis,E.Kartsakli,A. Antonopoulos,L. Alonso and C.Verikoukis, “Connectivity Analysis in Clustered Wireless Sensor Networks Powered by Solar Energy,” in IEEE Transactions on Wireless Communications,vol.17,(4),pp.2389-2401,April 2018,Doi:

[10] Bharath,K.R. & Suresh, E. Design and implementation of improved fractional open circuit voltage based maximum power point tracking algorithm for photovoltaic applications.International Journal of Renewable Energy Research. Vol. 7. pp.1108-1113, 2017.

[11] Simbeye, Daudi.“A Wireless Sensor Network Based Solar Powered Harvesting System for Aquaculture” Scitech Research Organisation, Vol. 7, (2),2018.

[12] Sharma, Himanshu & Haque,Ahteshamul & Jaffery, Zainul.“Modeling and Optimisation of a Solar Energy Harvesting System for Wireless Sensor Network Nodes.”Journal of Sensor and Actuator Networks.Vol. 7, (40), 2018.Doi:

[13] Ali Basrah Pulungan,Risfendra,Wawan Purwanto, Hasan Maksum and Oktrizal Setiawan “Design and Development of Real Time Monitoring Single Axis Solar Tracker by using Internet Of Things” International Journal of GEOMATE, Vol.18, (69),pp. 81 – 87, May 2020.

[14] Joaquin Canada-Bago,Jose-Angel Fernandez-Prieto, Manuel-Angel Gadeo-Martos and Pedro Perez-Higueras “Knowledge-Based Sensors for Controlling A High-Concentration Photovoltaic Tracker” Sensors,20,1315, 2020.

[15] Fraternali, Francesco, Bharathan Balaji,Yuvraj Agarwal and Rajesh K. Gupta.“ACES - Automatic Configuration of Energy Harvesting Sensors with Reinforcement Learning.” ACM Journals, Vol.16, (4), 2020. Doi:

[16] Shresthamali,Shaswot & Kondo,Masaaki & Nakamura, Hiroshi.“Adaptive Power Management in Solar Energy Harvesting Sensor Node Using Reinforcement Learning.” ACM Transactions on Embedded Computing Systems.Vol.16,pp. 1-21,2017.Doi:

[17] Khiati, Mustapha & Djenouri,Djamel.“Adaptive Learning-Enforced Broadcast Policy for Solar Energy Harvesting Wireless Sensor Networks.”Computer Networks.Vol.143,pp. 263-274,2018.Doi:

[18] Han, C.;Lin,Q.;Guo,J.;Sun,L.;Tao, Z. “A Clustering Algorithm for Heterogeneous Wireless Sensor Networks Based on Solar Energy Supply.”Electronics, Vol. 7, (103),2018.Doi:

[19] Benedetti,David & Petrioli, Chiara & Spenza,Dora.GreenCastalia:An energy-harvesting-enabled framework for the Castalia,ResearchGate,2013.Doi:


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