Assessing awareness of IoT-driven strategies for poultry management in mitigating increased ambient heat in Enugu, Nigeria

Onuoha I. Okocha(1), Terser Sombu(2), Julie W. Zimoghen(3), Anthony N. Uwajimgba(4),


(1) Federal College of Education, Eha-Amufu, Enugu State
(2) Federal College of Education, Eha-Amufu, Enugu State
(3) Federal College of Education, Eha-Amufu, Enugu State
(4) Federal College of Education, Eha-Amufu, Enugu State
Corresponding Author

Abstract


The study examined awareness level of Internet of Things (IoT)-driven strategies in mitigating impacts of increased ambient heat load in poultry pens by poultry farmers in a smart city like Enugu, Nigeria. With the rising challenges of climate change, increased ambient heat load within poultry pens poses a significant threat to poultry production. Understanding farmers’ perception of impact of increased ambient heat load and their awareness of IoT-driven strategies for its mitigation is crucial for sustainable poultry system management in smart cities. Multi-stage random sampling technique was used to select 240 poultry farmers from the three Local Government Areas that make up Enugu City. A structured questionnaire was used to collect data from the respondents. Descriptive statistics and Likert rating scale were used to analyze the data. The study identified socio-demographic factors influencing farmers’ perception of impact of increased heat load and awareness/ adoption of IoT-driven mitigation strategies. Education level (45% secondary education), access to information (29.2%) and financial resources (22.9%) were key determinants. The findings revealed varying levels of awareness among poultry farmers regarding IoT-driven strategies while the constraints faced by farmers in implementing sustainable IoT-driven mitigation strategies included lack of awareness, lack of funding/high initial investment, limited access to technology, inadequate training, poor extension contact, water availability and climate variability. The study concluded that majority of poultry farmers shared similar perceptions about the impact of increased ambient heat load on poultry species but however were not aware of many of the IoT-driven strategies to mitigate the impact and were limited by a number of constraints or challenges to adopting IoT-driven mitigation strategies which altogether could improve poultry production system and help to achieve animal protein security in a smart city like Enugu, Nigeria. The study further recommended enlightenment of poultry farmers on the impact of increased ambient heat load on poultry species and available/sustainable/harmonized IoT-enabled guidelines or solutions to mitigate heat load in smart cities’ poultry production system.

Keywords


Smart-Cities, IoT, heat-load, mitigation, poultry

References


Abbas G, Jaffey S, Hashmi AH, & Tanveer AJ (2022). Prospects and Challenges of adopting and implementing smart technologies in poultry production. Pakistan Journal of Science 74(2).

Adger WN & Vincent K (2006). Uncertainty in adaptive capacity. Comptes Rendus Geosciences, 337:399-410

Annual Flood Outlook (AFO) (2021). Annual Publication of Nigeria Hydrological Services 2021.

Adewale IO (2023). Intensity of adaptation to heat stress in poultry farms: A behavioral analysis of farmers in Ondo State, Nigeria. Journal of Thermal Biology 115. Available at https://doi.org/10.10164/j.thrbio.2023.103614

Annual Flood Outlook (AFO) (2021). Annual Publication of Nigeria Hydrological Services 2021.

Babayemi OJ, Ajayi MO, Akinsola SO, & Dauda MO (2017). Assessment of meat demand: A

case study of University of Ibadan for beef enterprise. Nigerian Journal of Animal Production, 44(3), 186-193.

Below TB, Mutabazi KD, Kirchke D, Franke C, Sieber S, Sirbert R, & Tscherning K (2012). Can farmer’s adaptation to climate change be explained by socio-economic household-level variables? Global Environmental Change (22) pp. 223-235.

Bu F & Wang X (2019). A smart agriculture IoT system based on deep reinforcement learning. J.

Future Generation Computer Systems (99), 500-507. https://doi.org/10.1016/j.future.2019.04.041

Chen Y, Liu X, & Li Z (2020). Development of an IoT-based smart feeding system for poultry. Journal of Intelligent Information Systems, 57(2), 257-271.

Chiemeke SC (2024). Smart Cities and Emerging Technologies. Lead Paper Presentation at the 5th Scientific Conference of the Nigeria Academy of Science, 24th January 2024. Available at https://www.nas.org.ng

Deressa I, Hassan RM, Ringler C, Alemu T, & Yusuf M (2008). Determinants of farmers’ choice of adaptation method to climate change in the Nile Basin of Ethiopia. Global Environ. Change, 19(2), pp. 248-255. https://www.doi.org/10.1016/j.gloenvcha.2009.01.002

ENADP (2021). Enugu State Agricultural Development Program, Annual Report. Pp. 35. Published by Enugu State Government of Nigeria.

Enugu State Government Official Gazette (1997). Enugu State Official Gazette No. 25.

Enete IC (2014). Impacts of climate change on agricultural production in Enugu State, Nigeia. J. Earth Sci. Clim. Change 5:234 https://doi.10.4172/2157-7617.1000234

Ekwe KC (2019). Consumption frequency of selected Animal protein sources among rural households in Enugu State, Nigeria. Journal of Community and Communication Research. 4(2), 53-61.

Fatuase A & Ajibefun I (2014). Perception and adaptation to climate change among farmers in selected communities of Ekiti State, Nigeria. Gaziosmanpasa Universitesi Ziraat Fakultesi Dergisi, 31(3), pp. 100-113.

Food and Agricultural Organization (2020). Food and Nutrition. FAO Fifth World Food Survey, 11(2), 53-63. Food and Agricultural Organization.

Fusel HM & Klein RJT (2006). Climate Change vulnerability assessment: an evolution of conceptual thinking. Climate Change 75, 301-329.

George A & Stylianou A (2018). Evaluation of the radio as an agricultural information source in

rural areas. Journal of Agricultural and Food Information 19(4). Pp. 362-376.

Gunasekera K, Barero AN, Vasulan F, & Bryceson KP (2018). Experiences in building an IoT infrastructure for agricultural education. J. of Procedia Computer Science (135), 155-162. https://doi.org./10.1016/j.procs.2018.08.161

Hassan RM & Nhemachena C (2008). Determinants of African farmers’ strategies for adapting to climate change: multinomial choice analysis. Afri. J. Agric. Resour. Econ., 2(311-2016-552). Pp. 83-104.

Henr-Ukoha A, Ibekwe UC, Chidiebere-Mark NM, Ejike R, & Oparadim H (2013). Determinants of food security in female-headed households under tenure system in Abia State, Nigeria. Global Journal of Agricultural Research. 1(2):48-57.

Hsu T, Yang H, Chung Y, & Hsu C (2020). A creative IoT agriculture platform for cloud fog computing. J. of Sustainable Computing Informatics and Systems (28), 100285. https://doi.org/10.1016/j.suscom.2018.10.006

Ibok OW, Bassey NE, Atairet EA, & Obot O (2014). Food Security Determinants among Urban Food Crop Farming Households in Cross River State, Nigeria. Asian Journal of Agricultural Extension, Economics and Sociology. 3(1), 76-90.

Khanna A & Kaur S (2019). Evolution of Internet of Things (IoT) and its significant impact in the field of Precision Agriculture (157), 218-231. https://doi.org/10.1016/j.compag.2018.12.039

Lara LJ & Rostagno MH (2020). Heat stress in poultry: A review. Journal of Animal Science, 98(11), 1-12.

Mashaly MM & Abdel-Moneim AE (2018). Heat stress in poultry: A review. Journal of Animal

Science, 96(11), 4511-4523.

Nascimento ST & Naas IA (2020). IoT applications in poultry production: A review. Journal of Agricultural Science and Technology, 20(3), 537-548.

Okocha OI, Uloh EV, Ede AE, Uwajimgba AN, & Sombu T (2022) Socio-demographic Characteristics and Economics of Egg-farming Enterprise among households in Enugu East Local Government Area of Enugu State. Journal of Family and Society Research 1(2), December 2022, pp.150-158.

Ozor N & Nnaji C (2011). The role of extension in agricultural adaptation to climate change in Enugu State, Nigeria. Journal of Agricultural Extension and Rural Development 3(3), pp. 42-50. Available online at https://academicjournals.org/JAERD

Pathak A, AmazUddin M, Abedin MJ, Andersson K, & Mustafa R (2019). IoT based Smart System to support agricultural parameters: A case study. J. Procedia Computer Science (155), 648-653. https://doi.org/10.1016/j.procs.2019.08.092

Roberts JR & Ball W (1998). Effect of Heat Stress on Egg and Egg Shell Quality in five Strains of laying hen. Proc. Aust. Poult. Sci. Sym. 53(2):295-296

Verdouw C, Sundmaeker H, Tekinerdogan B, Conzon D, & Montanaro T (2019). Architecture framework of IoT-based food and farm systems: A multiple case study. J. of Computers and Electronics in Agriculture (165). https://doi.org/10.1016/j.compag.2019.104939,

Wang L, Nishida H, Ogawa Y, & Konishi T (2020). Prevention of oxidative injury in PC12 cells by a traditional Chinese medicine, Shengmai San, as a model of an antioxidant-based composite formula. Biological and Pharmaceutical Bulletin, 26(7):1000-1004.


Full Text: PDF

Article Metrics

Abstract View : 36 times
PDF Download : 19 times

DOI: 10.57046/RBET5362

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Proceedings of the Nigerian Academy of Science

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.