Please wait a minute...
Big Data Mining and Analytics  2021, Vol. 4 Issue (1): 10-17    DOI: 10.26599/BDMA.2020.9020017
Special Issue on Intelligent Recommendation System and Big Data Analysis     
Intelligent Monitoring System for Biogas Detection Based on the Internet of Things: Mohammedia, Morocco City Landfill Case
Jamal Mabrouki*(),Mourade Azrour(),Ghizlane Fattah(),Driss Dhiba(),Souad El Hajjaji()
Laboratory of Spectroscopy, Molecular Modeling, Materials, Nanomaterial, Water and Environment, CERNE2D, Faculty of Science, Mohammed V University in Rabat, Rabat 10000, Morocco.
IDMS Team, Department of Computer Science, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia 52000, Morocco.
Civil Hydraulic and Environmental Engineering Laboratory, Mohammadia High School of Engineers, Agdal Rabat 10090, Morocco.
International Water Research Institute IWRI, University Mohammed VI Polytechnic (UM6P), Benguerir 43150, Morocco.
Download: PDF (1847 KB)      HTML  
Export: BibTeX | EndNote (RIS)      


Mechanization is a depollution activity, because it provides an energetic and ecological response to the problem of organic waste treatment. Through burning, biogas from mechanization reduces gas pollution from fermentation by a factor of 20. This study aims to better understand the influence of the seasons on the emitted biogas in the landfill of the city Mohammedia. The composition of the biogas that naturally emanates from the landfill has been continuously analyzed by our intelligent system, from different wells drilled in recent and old waste repositories. During the rainy season, the average production of methane, carbon dioxide, and oxygen and nitrogen are currently 56%, 32%, and 1%, respectively, compared to 51%, 31%, and 0.8%, respectively, for old waste. Hazards levels, potential fire, and explosion risks associated with biogas are lower than those of natural gases in most cases. For this reason a system is proposed to measure and monitor the biogas production of the landfill site remotely. Measurement results carried out at various sites of the landfill in the city of Mohammedia by the system show that the biogas contents present dangers and sanitary risks which are of another order.

Key wordsInternet of Things (IoTs)      biogas      monitoring      composition      detection      landfill     
Received: 11 June 2020      Published: 12 January 2021
Corresponding Authors: Jamal Mabrouki     E-mail:;;;;
About author: Jamal Mabrouki received the PhD degree in water science and technology from Faculty of Sciences, Mohamed V University in Rabat, Morocco in 2020. He is currently a researcher for the environment and climate program at ECOMED in Morocco, where he started the coordinator of the project "Adaptation of Citizens to Climate Change". He is an engineer in environment and climate. He is working on the project of migration and water and has the role of water governance in migration policy in Africa with the cooperation between MedYWat and World Bank. His research interests include environmental studies, energy and water treatment and pollution studies, wastewater treatment processes, smart environmental systems, innovative technologies, solid waste recovery, modelling and simulation, climate change, etc.|Mourade Azrour received the PhD degree from Faculty of Sciences and Technologies, Moulay Ismail University, Errachidia, Morocco in 2019, and the MS degree in computer and distributed systems from Faculty of Sciences, Ibn Zouhr University, Agadir, Morocco in 2014. He currently works as a computer science professor at the Department of Computer Science, Faculty of Sciences and Technologies, Moulay Ismail University. His research interests include authentication protocol, computer security, Internet of Things, and smart systems. He is a scientific committee member of numerous international conferences. He is also a reviewer of various scientific journals, such as International Journal of Cloud Computing and International Journal of Cyber-Security and Digital Forensics (IJCSDF).|Ghizlane Fattah received the BS degree in water science from the Sidi Mohamed Ben Abdellah University in 2008 and the MS degree in engineering and management of water and environment from the Mohammed V University, Rabat, in 2010. Since December 2017, she is a PhD candidate in environmental engineering at Mohammadia High School of Engineers, Rabat, Morocco. She has worked as a freelance environmental consultant for more than a year, then she joined the society "Group of Consultants and Engineers of Morocco" as an engineer in charge of environmental studies for five years and grew to be a project chief engineer in environment at this society. Her research interests include environmental studies, civil engineering, water technologies, and climate change.|Driss Dhiba received the PhD degree in agro-resources valorization from Intstitut National Polytechnique de Toulouse, Toulouse, France in 1995. He has been carrying out several research projects related to chemical engineering, water treatment and reuse, environment, biotechnology, fertilizers technologies, trace elements recovery, and new products development. He joined University Mohammed 6 Polytechnic (UM6P) in 2017 as a science & technology adviser and he is currently the co-leader of Water & Climate Program at the International Water Research Institute. His research interests include water treatment techniques, environmental studies, and climate change studies.|Souad El Hajjaji received the PhD degree in material sciences from the National Polytechnique Institute of Toulouse in 1994 and the PhD degree from University Mohammed V University in Rabat, Morocco in 1999. Currently, she is a full professor at Faculty of Sciences, Mohamed V University in Rabat and the head of Research Centre on Water, Natural Resource, Environment and Sustainable Development. Her research interests including water quality, water pollution, wastewater treatment processes (adsorption, photocatalysis, etc.), innovative technologies, solid waste valorisation, modelling, climate change, etc.
Cite this article:

Jamal Mabrouki,Mourade Azrour,Ghizlane Fattah,Driss Dhiba,Souad El Hajjaji. Intelligent Monitoring System for Biogas Detection Based on the Internet of Things: Mohammedia, Morocco City Landfill Case. Big Data Mining and Analytics, 2021, 4(1): 10-17.

URL:     OR

Fig. 1 Study site localisation.
Fig. 2 Architecture of the proposed system.
Fig. 3 (a) Bluetooth module HC-05 and (b) ESP8266 pin details.
Fig. 4 Sensors used in the system.
Fig. 5 Characterization of Mohammedia landfill biogas.
SiteMajor components of biogas
CH4 (%)CO2 (%)N2 (%)O2 (%)H2S (10-6)
Site 356.
Table 1 Variation in the composition of biogas in the sites.
[1]   Harrison S., Volunteered geographic information for people-centred severe weather early warning: A literature review, Australasian Journal of Disaster and Trauma Studies, vol. 24, no. 1, pp. 3-22, 2020.
[2]   Mcclintock R., Power and pedagogy: Transforming education through information technology, Report, Institute of Learning Technologies, New York, NY, USA, 1992.
[3]   Bauquis P. R., A reappraisal of energy supply and demand in 2050, Oil & Gas Science and Technology, vol. 56, no.4, pp. 389-402, 2001.
[4]   Chen Y., Wang Z., and Zhong Z., CO2 emissions, economic growth, renewable and non-renewable energy production and foreign trade in China, Renewable Energy, vol. 131, pp. 208-216, 2019.
[5]   Ortega D. R. and Subrenat A., Siloxane treatment by adsorption into porous materials, Environmental Technology, vol. 30, no. 10, pp. 1073-1083, 2009.
[6]   Wirth R., Kovács E., Maróti G., Bagi Z., Rákhely G., and Kovács K. L., Characterization of a biogas-producing microbial community by short-read next generation DNA sequencing, .
doi: 10.1186/1754-6834-5-41
[7]   Lampinen A., Biogas farming: An energy self-sufficient farm in Finland, Refocus, vol. 5, no. 5, pp. 30-32, 2004.
[8]   Wellinger A. and Linberg A., Biogas upgrading and utilisation-IEA Bioenergy, Task 24-Energy from biological conversion of organic waste, Report, IEA Bioenergy, Paris, France, 2000.
[9]   Gabelica V., Shvartsburg A. A., Afonso C., Barran P., Benesch J. L., Bleiholder C., Bowers M. T., Bilbao A., Bush M. F., Campbell J. L., et al., Recommendations for reporting ion mobility mass spectrometry measurements, Mass Spectrometry Reviews, vol. 38, no. 3, pp. 291-320, 2019.
[10]   Prebihalo S. E., Berrier K. L., Freye C. E., Bahaghighat H. D., Moore N. R., Pinkerton D. K., and Synovec R. E., Multidimensional gas chromatography: Advances in instrumentation, chemometrics, and applications, Analytical Chemistry, vol. 90, no. 1, pp. 505-532, 2018.
[11]   Taguchi N., Japanese Patent Application No. 45-38200 (1962); Shimizu Y., Nakamura Y., and Egashira M., Sensor and Actuators B., vol. 13, no. 14, pp. 128-199, 1993.
[12]   Farki K. and Zahour G., Contribution to the understanding of the sedimentary and tectono-volcanological evolution of Oued Mellah, in Proc. of Colloque International Conference of SIG Users, Taza GIS-Days, Coast Meseta, Morocco, 2012, pp. 568-572.
[13]   Nikiema J., Brzezinski R., and Heitz M., Elimination of methane generated from landfills by biofiltration: A review, Reviews in Environmental Science and Bio/Technology, vol. 6, no. 4, pp. 261-284, 2007.
[14]   Jung Y., Imhoff P. T., Augenstein D. C., and Yazdani R., Influence of high-permeability layers for enhancing landfill gas capture and reducing fugitive methane emissions from landfills, Journal of Environmental Engineering, vol. 135, no. 3, pp. 138-146, 2009.
[15]   Yang M., Davies C., Alkane P. L. C., and Hadro U. M. J., New trends in coalmine methane recovery and utilization, Chemical Engineering Science, vol. 100, no. 11, pp. 21-26, 2008.
[16]   Grabow M. L., Spak S. N., Holloway T., Jr B. S., Mednick A. C., and Patz J. A., Air quality and exercise-related health benefits from reduced car travel in the midwestern United States, Environmental Health Perspectives, vol. 120, no. 1, pp. 68-76, 2012.
[17]   Belhaj S., Presentation du calcul de la ligne de base du projet pilote MDP: Decharge Akreuch, Report, Cleantech, Rabat, Morocco, 2004.
[18]   Mabrouki J., Azrour M., Farhaoui F., El Hajjaji S., Intelligent system for monitoring and detecting water quality, Big Data and Networks Technologies, vol. 81, pp. 172-182. 2020.
[19]   Srivastava P., Bajaj M., and Rana A. S., Overview of ESP8266 Wi-Fi module-based smart irrigation system using IOT, .
doi: 10.1109/AEEICB.2018.8480949
[20]   Mukesh D. M. and Akula S. K., Automated indoor air quality monitor and control, International Journal of Computer Applications, vol. 159, no. 6, pp. 33-38, 2017.
[21]   Zanella A., Bui N., Castellani A., Vangelista L., and Zorzi M., Internet of things for smart cities, IEEE Internet of Things Journal, vol. 1, no. 1, pp. 22-32, 2014.
[22]   Li H. Y. and Chen C. Z., The development of underground personnel data terminal based on RSSI location, doi: 10.4028/
[23]   Dang C. T., Seiderer A., and André E., Theodor: A step towards smart home applications with electronic noses, in Proceedings of the 5th International Workshop on Sensor-based Activity Recognition and Interaction, Berlin, Germany, 2018, pp. 1-7.
[24]   Tadano K., Yuzuriha T., Sato T., Fujita T., Shimada K., Hashimoto K., and Sath K., Identification of menaquinone-4 metabolites in the rat, Journal of Pharmacobio-Dynamics, vol. 12, no. 10, pp. 640-645, 1989.
[25]   Lyu D.-P., Zheng J.-Y., Li Q.-W., Liu J. L., Chen Y. C., Jia J. H., and Tong M. L., Construction of lanthanide single-molecule magnets with the “magnetic motif” [Dy(MQ)4], Inorganic Chemistry Frontiers, vol. 4, no. 11, pp. 1776-1782, 2017.
[26]   Cheng S., Li Z., Mang H.-P., and Huba E.-M., A review of prefabricated biogas digesters in China, Renewable and Sustainable Energy Reviews, vol. 28, pp. 738-748, 2013.
[27]   Yau H. T. and Menq C. H., An automated dimensional inspection environment for manufactured parts using coordinate measuring machines, The International Journal of Production Research, vol. 30, no. 7, pp. 1517-1536, 1992.
[28]   Naminata S., Kwa-Koffi K. E., Marcel K. A., and Marcellin Y. K., Assessment and impact of leachate generated by the landfill city in Abidjan on the quality of ground water and surface water, Journal of Water Resource and Protection, vol. 10, no. 1, p. 145, 2018.
[1] Wei Zhong, Ning Yu, Chunyu Ai. Applying Big Data Based Deep Learning System to Intrusion Detection[J]. Big Data Mining and Analytics, 2020, 3(3): 181-195.
[2] Jingshu Liu, Li Wang, Jinglei Liu. Efficient Preference Clustering via Random Fourier Features[J]. Big Data Mining and Analytics, 2019, 2(3): 195-204.
[3] Leilei Shi, Yan Wu, Lu Liu, Xiang Sun, Liang Jiang. Event Detection and Identification of Influential Spreaders in Social Media Data Streams[J]. Big Data Mining and Analytics, 2018, 1(1): 34-46.
[4] Baojun Zhou, Jie Li, Xiaoyan Wang, Yu Gu, Li Xu, Yongqiang Hu, Lihua Zhu. Online Internet Traffic Monitoring System Using Spark Streaming[J]. Big Data Mining and Analytics, 2018, 1(1): 47-56.
[5] Jin Liu, Yi Pan, Min Li, Ziyue Chen, Lu Tang, Chengqian Lu, Jianxin Wang. Applications of Deep Learning to MRI Images: A Survey[J]. Big Data Mining and Analytics, 2018, 1(1): 1-18.
[6] Ziling Pang, Guoyin Wang, Jie Yang. A Multi-granularity Decomposition Mechanism of Complex Tasks Based on Density Peaks[J]. Big Data Mining and Analytics, 2018, 01(03): 245-256.