Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 Approaches to smart village development might varies due to the uniquesness in smart village developments and other influencing factors. While smart villages are not extensions of smart cities, this makes rural challenges area specific with defined plans. + 2381 word(s) 2381 2020-11-11 09:45:26 |
2 format change -263 word(s) 2118 2020-12-01 09:26:36 | |
3 format change -263 word(s) 2118 2020-12-01 09:30:37 |

Video Upload Options

Do you have a full video?


Are you sure to Delete?
If you have any further questions, please contact Encyclopedia Editorial Office.
Adesipo, A.; Fadeyi, O.; Kuca, K.; Krejcar, O.; Maresova, P.; Selamat, A.; Adenola, M. Smart village. Encyclopedia. Available online: (accessed on 20 June 2024).
Adesipo A, Fadeyi O, Kuca K, Krejcar O, Maresova P, Selamat A, et al. Smart village. Encyclopedia. Available at: Accessed June 20, 2024.
Adesipo, Adegbite, Oluwaseun Fadeyi, Kamil Kuca, Ondrej Krejcar, Petra Maresova, Ali Selamat, Mayowa Adenola. "Smart village" Encyclopedia, (accessed June 20, 2024).
Adesipo, A., Fadeyi, O., Kuca, K., Krejcar, O., Maresova, P., Selamat, A., & Adenola, M. (2020, November 30). Smart village. In Encyclopedia.
Adesipo, Adegbite, et al. "Smart village." Encyclopedia. Web. 30 November, 2020.
Smart village

In this study, the level of progress of climate smart agriculture was examined, its ideas were employed to develop a framework for smart village development. This is essential because most agricultural activites are maximized in the rural communities, more so, its development can influence the increasing rural-urban migration. Also of importance is the tailoring of this framework towards sustainability. 

Smart Village Smart agriculture Climate smart agriculture Sustainability Rural-urban migration

1. Introduction

The need to develop rural communities in terms of productivity and convenience, so as to curb urban migration has received much attention in the last decade. First, the Institute of Electrical and Electronics Engineers (IEEE), as part of its mission, commenced the installation of solar-powered bulbs in many rural communities worldwide[1]. This was followed in 2016 by the Cork Declaration, agreed amongst 340 representatives of European states towards ensuring that rural communities enjoy better lives. These efforts culminated into the coining of the word “smart village”, defined as a community that tries to develop current strength and resources, while making futuristic developmental plans on the basis of technology[2][3]. While there are several thematic areas of priority within the smart village development framework, agriculture is seen as the most important of them all[3]. Furthermore, the need to bridge the digitization gap between cities and villages, is also an important aspect, so that lives and livelihood can be improved. Since a smart village is one that seemingly accepts new technologies, precision agriculture uses ultra-modern techniques for animal and crop production, which saves time and reduces wastage, and meets the requirements of smart villages. This is crucial for the sustainability of smart villages[4]. This is because improved food production and efficient animal management systems must be at par with village development, and must be continually transformed to influence the different aspects of smart villages, in terms of policy and practice[5].

To effectively play its role in smart villages, precision agriculture covers smart and climate smart agriculture (CSA) techniques, and other aspects that are capable of ensuring higher agricultural production output in an environment-friendly manner, provides optimum income for the farmer, and is able to feed a growing population. Many studies showed that these processes can be realized through the adoption of ultra-modern agricultural techniques such as bio and nano technologies[6], IoT and blockchain-based methods[7], and drone technologies[8], among other climate smart ideas. On the basis of this argument, efforts that tend to reduce farming losses, increase yield, as well as monitor, detect, and potentially prevent plant and animal diseases are now being automated, finding growing applications, and offering optimal solutions. Based on the forgone explanations, the current study attempts to establish smart and CSA trends

2. Moving towards Climate-Smart Agriculture

Having established in Section 2.1 that agriculture is one of the most important factors to be considered in smart village development, it is crucial to stress that climate change is a major stressor for agricultural development of rural communities[9]. The implication is that developing an agriculturally-smart village entails accepting the concept of climate-smart agriculture. Agricultural risk posed by climate is a threat to food security. As a result, there is an urgent need to effectively manage agricultural production, while fighting climate change through adaptation, resilience and mitigation[10]. This is what climate-smart agriculture offers.

There is currently no unified definition for climate-smart agriculture (CSA). In fact, almost every new study within the framework of smart-agriculture, views CSA in a slightly unique way. Nevertheless, to build a strong foundation for climate-smart agricultural framework in smart village development, the current study adopts existing knowledge and definitions, to coin a new and more robust definition for the term. Table 2 presents some definitions put forward by climate change and agricultural scholars and research organizations. Keywords derived from the definitions show that each has one or more shortcomings. As a result, it might be difficult to build the concept of smart village on a definition that lacks one or more fundamental aspects.

Table 2. Definitions of CSA.




The combination of activities that helps to: build adaptive measures that increase productivity, increase resilience to stresses posed by climatic change, and reduce GHG emissions.

Capacity building; emission reduction


A sustainable method through which improved productivity and income is achieved in agricultural production via the adoption of adaptation, resilience and GHG emissions mitigation

Sustainability; Emission reduction; productivity; profit; capacity building


Processes that transform agricultural systems to boost food security, given current changes in climate

Productivity; transformation; food security


A system of agriculture that supports emission reduction while creating improved productivity profits, nonetheless reducing vulnerability

Vulnerability reduction; emission reduction; profit growth


A system of agriculture that improves production in a sustainable manner, while building capacity to ward-off agricultural and climate change challenges

Sustainability; capacity building; productivity


Strategies that are able to curb agricultural challenges through the increment of resilience activities to extreme weather conditions, building adaptive capacities to climate change and mitigating agriculture-based GHG emission increase.

Capacity building; emission reduction.


Practices that add to improved food security globally, and further enable farmers to effectively adapt to the incidence of climate change and global emission levels

Capacity building; emission reduction; food security


Combined use of ultramodern technologies and processes that work together to boost farming productivity and incomes, while increasing the farm’s and farmers’ ability to manage climate change through GHG emission reduction.

New technology adoption; productivity, profit; capacity development; emission reduction


A technique that combines a number of sustainable techniques to fight particular climate challenges within a specified farming area

Sustainability; GHG emission reduction


An agricultural framework that tries to develop and adopt technique that will improve rural livelihoods, food security, and facilitate adaptation to climate change, while also providing mitigation benefits

New knowledge; food security; capacity building.



Given the definitions in Table 2, considerable aspects of climate-smart agriculture include; capacity building, sustainability, emission reduction, vulnerability reduction, profit, food security, transformation, new knowledge, new technology, and productivity. By linking the above keywords together, we define climate-smart agriculture as a “transformative and sustainable kind of agriculture that tries to increase efficiency (productivity) in food security and production systems, using a combination of the pillars of climate change (adaptation, resilience, and mitigation) as well as smart and new technological knowledge, that do not only build capacity of farmers’ in terms of farming techniques, but also increase profit, reduces vulnerability of the systems as well as their results (farm products/animals), through the reduction of GHG emissions.”

While it can be argued that the list of keywords suggested within the current study is not exhaustive, many other definitions tend to be built around at least one of these keywords. Figure 1 is a diagrammatical representation of the main aspects of climate-smart agriculture for which it stands as a significant part of a smart village. The implication of the above expository listing of the fundamental parts of climate-smart agriculture means that for a smart village to be so called, it must strive to maintain within its agricultural systems all different aspects of CSA. Furthermore, other aspects of the smart culture within the smart village setting; smart energy management, smart living and smart healthcare, etc., must tap from these fundamental attributes of CSA, in order to provide robust services in their smart village functions.

Figure 1. Key aspects of climate-smart agriculture (CSA).

In demonstrating whether CSA could increase rice yield in China, Xiong et al.[20] used crop simulation models; version 0810 of the Environmental Policy Integrated Climate (EPIC) model[21], and version 4.0 of the so-called DSSAT, an acronym for Decision Support System for Agro-technology Transfer[22], respectively. It was observed that these software simulations that gave ideas on cultivar improvement and optimization of management practices for rice due to climate change, led to increased rice production. The EPIC models specifically yielded over 2000 kgha−1 during the 30-year period under review[20].

Rural African farmers tend to suffer a lot from adverse weather conditions. This further creates a need for cheap and reliable weather forecast system. To attend to such needs in Nigeria[23], a cheap automatic weather station that functions on solar energy was designed. By linking meteorological sensors to microcontrollers, the farmer could gain access to processed information related to weather, through a television screen. A thermometer collects temperature information, while the anemometer and LDR measures wind speed and sunlight, respectively. Embedded temperature sensors within the microcontroller receives analog information gathered by the thermometer and converts it to digital signals[23] In some cases, unprocessed data can also be sent to farmer’s mobile phones. The cheap rate of the unit shows that it can serve as a very good system for crop management and food security, in the least developed nations.

In a research carried out by Tenzin et al.[24], to ensure effective weather monitoring around a farm, the authors designed a very cheap cloud-based weather measurement unit, using an integration of different unique weather sensors. The system, which is made up of a base and a weather station, as well as a display unit, is capable of effectively gathering humidity, temperature, wind direction, wind speed, and many other weather data types. By experimenting its usage and statistically analyzing gathered data, it was observed that the unit provided similar results as the Davis Vantage Pro2 weather monitor, which was pre-installed on the same farm, thus, offering a cheaper option[24].

In a bid to design an integrated farm that efficiently manages water and reduces climate-demanding inputs, Doyle et al.[25] designed an aquaponics unit for vegetables and fish. The design consists of a 12V DC pump that delivers water from the fish tank to the flood tank, which then supplies the area where the crops are planted at a constant rate. As soon as water is removed from the fish pond, it is carried by gravity through the grow bed area, where it is stored until it is needed for watering the vegetable bed. The pump is powered using a solar panel of 150-Watt with a 120 Ah battery.

Having described some smart agricultural and climate-smart agricultural studies, it is important to note that while smart agriculture is mostly developed, research on CSA is relatively new and still at the level of policy and framework description[26]. In a systematic review study by Chandra et al.[26], the authors observed that research on CSA is mainly divided into three parts; global policy and plans around the world concerning further development of the concept, scientific research directions, and integration of pillars of the concept (which includes; adaptation, resilience, mitigation, and food security). With respect to CSA policy framework developed by the World Bank, Taylor[27]faulted the fundamental make-up of the concept on the following grounds.

  • There are no explicit conditions that can be referred to as success of CSA, which makes certain fundamental aspects like productivity, completely implicit.
  • Being an important part of sustainability, resilience as pointed out within World Bank’s CSA framework is not defined, thus, leaving the term implicit.
  • Given an absence of conceptual framework for CSA, literature relating to the topic are merely based on success stories of some normative research on agricultural improvement.
  • CSA tries not to be involved with how consumer sovereignty influences food production around the world, towards the consumption demands of the elite.

Given these fundamental shortcomings of CSA[27]‘climate-wise food system’ is suggested as a more direct term that should be used to refer to sustainable food production systems, rather than CSA. Another criticism on the policy and framework of CSA comes with the injustice meted to smallholder farmers, as a result of the implementation of the concept[28]. By administering interview to some CSA experts, analysis based on a number of ethical positions showed that implementation of climate-smart agricultural approaches is not fair, especially with respect to allocation of income benefits and challenges of cost associated with emission reduction [87], among smallholders farmers and small agricultural processing industries. Budiman[28] further argued that based on how climate justice works, sharing of income benefits should depend on the financial capability of farmers.

In a comparative study of Philippines and Timor-Leste, five important features of climate-smart agricultural practices were observed by Chandra and McNamara[29]; strategies at country-specific institutional levels; delegated financial procedures; the state of the market; technology; and knowledge. In the two countries, CSA was used to resolve climate vulnerability challenges more than it was associated with emission reduction goals[29]. Overall, the researchers observed that advancing the course of CSA in these countries might involve multi-stakeholder approaches that cuts across different levels of participation, both within and outside the farm, rather than mere technical CSA developmental inputs[29]. From the above arguments for and against CSA, it is clear that while there are still fundamental challenges revolving round the CSA concept, the terms might likely continue to be utilized for agricultural problem solving, until it attains uniformity and intersection of ideologies, amongst researchers and policy makers.


  1. Mackenzie, D. IEEE Smart Village Sustainable Development Is a Global Mission. IEEE Syst. Man Cybern. Mag. 2019, 5, 39–41, doi:10.1109/MSMC.2019.2916248.
  2. Jung, J.G. Smart Communities: Digitally-Inclined and Content-Rich. Available online: (accessed on 27 May 2020).
  3. European Commission EU Support for Smart Villages. European Commission-European Commission. 4 August 2019. Available online: (accessed on 3 June 2020).
  4. Maheswari, R.; Azath, H.; Sharmila, P.; Gnanamalar, S.S.R. Smart Village: Solar Based Smart Agriculture with IoT Enabled for Climatic Change and Fertilization of Soil. In Proceedings of the 2019 IEEE 5th International Conference on Mechatronics System and Robots (ICMSR), Singapore, 3–5 May 2019; pp. 102–105, doi:10.1109/ICMSR.2019.8835454.
  5. Azevedo, D. Precision Agriculture and the Smart Village Concept. In Smart Villages in the EU and Beyond; Visvizi, A., Lytras, M.D., Mudri, G., Eds.; Emerald Publishing Limited: Bingley, UK, 2019; pp. 83–97.
  6. Antonacci, A.; Arduini, F.; Moscone, D.; Palleschi, G.; Scognamiglio, V. Nanostructured (Bio)sensors for smart agriculture. TrAC Trends Anal. Chem. 2018, 98, 95–103, doi:10.1016/j.trac.2017.10.022.
  7. Khoa, T.A.; Man, M.M.; Nguyen, T.-Y.; Nguyen, V.; Nam, N.H. Smart Agriculture Using IoT Multi-Sensors: A Novel Watering Management System. J. Sens. Actuator Netw. 2019, 8, 45, doi:10.3390/jsan8030045.
  8. Mogili, U.R.; Deepak, B.B.V.L. Review on Application of Drone Systems in Precision Agriculture. Procedia Comput. Sci. 2018, 133, 502–509, doi:10.1016/j.procs.2018.07.063.
  9. Campbell, B.M.; Thornton, P.; Zougmoré, R.; van Asten, P.; Lipper, L. Sustainable intensification: What is its role in climate smart agriculture? Curr. Opin. Environ. Sustain. 2014, 8, 39–43, doi:10.1016/j.cosust.2014.07.002.
  10. Aggarwal, P.K.; Jarvis, A.; Campbell, B.M.; Zougmoré, R.B.; Khatri-Chhetri, A.; Vermeulen, S.; Loboguerrero Rodriguez, A.M.; Sebastian, L.; Kinyangi, J.; Bonilla Findji, O.; et al. The climate-smart village approach: Framework of an integrative strategy for scaling up adaptation options in agriculture. Ecol. Soc. 2018, 23, doi:10.5751/ES–09844–230114.
  11. Food and Agriculture Organization. Climate Smart Agriculture: Policies, Practices and Financing For Food Security, Adaptation and Mitigation; Food and Agriculture Organization of the United Nations: Rome, Italy, 2010.
  12. Food and Agriculture Organization. Climate-Smart Agriculture Sourcebook; Food and Agriculture Organization of the United Nations: Rome, Italy, 2013.
  13. Engel, S.; Muller, A. Payments for environmental services to promote ‘climate-smart agriculture’? Potential and challenges. Agric. Econ. 2016, 47, 173–184, doi:10.1111/agec.12307.
  14. Rosenstock, T.S.; Lamanna, C.; Chesterman, S.; Bell, P.; Arslan, A.; Richards, M.; Rioux, J.; Akinleye, A.O.; Champalle, C.; Cheng, Z.; et al. The Scientific Basis of Climate-Smart Agriculture: A Systematic Review Protocol; CGIAR Research Program on Climate Change; CCAFS Working Paper; Agriculture and Food Security (CCAFS): Copenhagen, Denmark, 2016; p. 138. Available online: (accessed on 17 November 2019).
  15. Steenwerth, K.L.; Hodson, A.K.; Bloom, A.J.; Carter, M.R.; Cattaneo, A.; Chartres, C.J.; Hatfield, J.L.; Henry, K.; Hopmans, J.W.; Horwath, W.R. Climate-smart agriculture global research agenda: Scientific basis for action. Agric. Food Secur. 2014, 3, 11, doi: 10.1186/2048-7010-3-11.
  16. Hellin, J.; Fisher, E. Building pathways out of poverty through climate smart agriculture and effective targeting. Dev. Pract. 2018, 28, 974–979, doi:10.1080/09614524.2018.1492516.
  17. Rao, N.H. Big Data and Climate Smart Agriculture-Status and Implications for Agricultural Research and Innovation in India. Proc. Indian Natl. Sci. Acad. 2018, 84, 625–640, doi:10.16943/ptinsa/2018/49342.
  18. Alliance, R. What Is Climate-Smart Agriculture? Rainforest Alliance: 2020. Available online: (accessed 5 June 2020).
  19. Scherr, S.J.; Shames, S.; Friedman, R. From climate-smart agriculture to climate-smart landscapes. Agric. Food Secur. 2012, 1, 12, doi:10.1186/2048-7010-1-12.
  20. Xiong, W.; van der Velde, M.; Holman, I.P.; Balkovic, J.; Lin, E.; Skalský, R.; Porter, C.; Jones, J.; Khabarov, N.; Obersteiner, M. Can climate-smart agriculture reverse the recent slowing of rice yield growth in China? Agric. Ecosyst. Environ. 2014, 196, 125–136, doi:10.1016/j.agee.2014.06.014.
  21. William, J.R. The EPIC model. In Computer Models in Watershed Hydrology; Singh, V.P., Ed.; Water Resources Publication, LLC: Highlands Ranch, CO, USA, 2012; pp. 909–100.
  22. Jones, J.W.; Hoogenboom, G.; Porter, C.H.; Boote, K.J.; Batchelor, W.D.; Hunt, L.A.; Wilkens, P.W.; Singh, U.; Gijsman, A.J.; Ritchie, J.T. The DSSAT cropping system model. Eur. J. Agron. 2003, 18, 235–265, doi:10.1016/S1161-0301(02)00107-7.
  23. Adoghe, A.U.; Popoola, S.I.; Chukwuedo, O.M.; Airoboman, A.E.; Atayero, A.A. Smart Weather Station for Rural Agriculture using Meteorological Sensors and Solar Energy. In Proceedings of the World Congress on Engineering, London, UK, 5–7 July 2017; Volume I, pp. 1–4. Available online: (accessed on 7 June 2020).
  24. Tenzin, S.; Siyang, S.; Pobkrut, T.; Kerdcharoen, T. Low cost weather station for climate-smart agriculture. In Proceedings of the 2017 9th International Conference on Knowledge and Smart Technology (KST), Chonburi, Thailand, 1–4 February 2017; pp. 172–177, doi:10.1109/KST.2017.7886085.
  25. Doyle, L.; Oliver, L.; Whitworth, C. Design of a Climate Smart Farming System in East Africa. In Proceedings of the 2018 IEEE Global Humanitarian Technology Conference (GHTC), San Jose, CA, USA, 18–21 October 2018; pp. 1–6, doi:10.1109/GHTC.2018.8601553.
  26. Chandra, A.; McNamara, K.E.; Dargusch, P. Climate-smart agriculture: Perspectives and framings. Clim. Policy 2018, 18, 526–541, doi:10.1080/14693062.2017.1316968.
  27. Taylor, M. Climate-smart agriculture: What is it good for? J. Peasant Stud. 2018, 45, 89–107, doi:10.1080/03066150.2017.1312355.
  28. Budiman, I. Climate-smart agriculture policy and (in)justice for smallholders in developing countries. Future Food-J. Food Agric. Soc. 2019, 7, 31–41, doi:10.17170/kobra-2018122074.
  29. Chandra, A.; McNamara, K.E. Climate-Smart Agriculture in Southeast Asia: Lessons from Community-Based Adaptation Programs in the Philippines and Timor-Leste. In Resilience: The Science of Adaptation to Climate Change; Zommers, Z., Alverson, K., Ed.; Elsevier Science BV: Amsterdam, The Netherlands, 2018; pp. 165–179.
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to : , , , , , ,
View Times: 1.2K
Revisions: 3 times (View History)
Update Date: 31 Dec 2020
Video Production Service