The Real-Time Alert System for Prayers at Smart Masjid

Tanweer Alam, Moath Erqsous


Arrange and monitor people in a crowded environment inside masjid is a critical task. It is necessary to fill rows start from first row behind the Imam. Most counting techniques depend on detecting individuals in order to count their number. Counting and arrangement becomes inefficient when it is required in real-time and when the crowd is dense. I am proposing a technique for monitoring and estimating the density of crowd in real-time using infrared technology. The intelligent systems will be designed based on the number of people section wise. The mosque will be divided into sections and each section will be allocated an Infra-Red Camera. Each section will be programmed to contain limited number of people. There will be an LED display allocated to each section. With the people coming into that section, the display will start becoming less GREEN. In other words, the intensity of the GREEN LED display will become weaker. As the section is completely filled, the display will turn red. This way, people could see the section from quite a distance and can easily decide whether to move forward or not. As soon as the people enter the mosque, they will have an overview of each section and can decide to go to the suitable places to get settled easily into the rows. Our pre-programmed thermal camera will recognize people on the basis of their body temperature. The LED display will go less green as the system receives more thermograms. After reaching the highest level of thermograms received, the LED display will automatically go RED. This would naturally stop people to enter that section.

Full Text:



. Kettani, H. (2010). Muslim population in europe: 1950-2020. International Journal of Environmental Science and Development, 1(2), 154.

. Al-Kodmany, K. (2009). Planning for the Hajj: political power, pragmatism, and participatory GIS. Journal of Urban Technology, 16(1), 5-45.

. Aljohani, A. M. (2015). Pilgrim crowd dynamics (Doctoral dissertation, University of Birmingham).

. Aqel, M. O., Issa, A., Nada, D. A., & Draz, S. (2018, October). Development of Smart Masjid Display Using Raspberry Pi. In 2018 International Conference on Promising Electronic Technologies (ICPET) (pp. 118-123). IEEE.

. Al-Khalifa, H. E. (2019). The Smart Mosque of the Arabian Gulf: Solutions from the past for a sustainable, energy-efficient Mosque.

. Alamri, R. J., Alkhuriji, M. S., Alshamani, M. S., Ibrahim, O. Y., & Haron, F. (2018, April). Al-Masjid An-Nabawi Crowd Adviser Crowd Level Estimation Using Head Detection. In 2018 1st International Conference on Computer Applications & Information Security (ICCAIS) (pp. 1-4). IEEE.

. Alshehri, A., Arif, M., & Felamban, E. (2016). Simulation of crowd in the corridor of ziara in Masjid-e-Nabwi, Madinah. In Traffic and Granular Flow'15 (pp. 353-360). Springer, Cham.

. Rossi, M., Cattari, S., & Lagomarsino, S. (2015). Performance-based assessment of the Great Mosque of Algiers. Bulletin of Earthquake Engineering, 13(1), 369-388.

. Shannahan, D. S. (2014). Gender, inclusivity and UK mosque experiences. Contemporary Islam, 8(1), 1-16.

. Hakim, N. (2008). Mosque architecture past and present. In Sacred Buildings. Birkhäuser Basel, Springer. pp. 46-53.

. Setiadi, H. (2015). Islam and Urbanism in Indonesia: The mosque as urban identity in Javanese Cities. In The Changing World Religion Map (pp. 2415-2436). Springer, Dordrecht.

. Yusarelan, M. N. A., Hamid, S. Z. A., Rashid, R. A., & Ibrahim, A. K. M. (2020, July). IoT Based Temperature Control for Smart Mosque. In IOP Conference Series: Materials Science and Engineering (Vol. 884, No. 1, p. 012079). IOP Publishing.

. Sumaryanto, T. (2016). Planning for The Smart Mosque as Islamic Learning Resources Center. Indonesian Journal of Islamic Literature and Muslim Society, 1(2), 167-180.

. Ciampa, F., Mahmoodi, P., Pinto, F., & Meo, M. (2018). Recent advances in active infrared thermography for non-destructive testing of aerospace components. Sensors, 18(2), 609.

. Haurum, J. B., & Moeslund, T. B. (2020). A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections. Automation in Construction, 111, 103061.

. McCarthy, A., Krichel, N. J., Gemmell, N. R., Ren, X., Tanner, M. G., Dorenbos, S. N., ... & Buller, G. S. (2013). Kilometer-range, high resolution depth imaging via 1560 nm wavelength single-photon detection. Optics express, 21(7), 8904-8915.

. Falco, C. M. (2009). Invited Article: High resolution digital camera for infrared reflectography. Review of scientific instruments, 80(7), 071301.

. Ma, J., Ma, Y., & Li, C. (2019). Infrared and visible image fusion methods and applications: A survey. Information Fusion, 45, 153-178.

. Nigam, R. K. (2018). Application of Thermal Imaging in Forensic Vision. Indonesian Journal of Legal and Forensic Sciences, 8(1), 15-18.

. Yu, Y., Mariotti d’Alessandro, M., Tebaldini, S., & Liao, M. (2020). Signal Processing Options for High Resolution SAR Tomography of Natural Scenarios. Remote Sensing, 12(10), 1638.

. Aljohani, M., & Alam, T. (2017). Real time face detection in ad hoc network of android smart devices. In Advances in Computational Intelligence (pp. 245-255). Springer, Singapore.

. Alam, T. (2020). CMI Computing: A Cloud, MANET, and Internet of Things Integration for Future Internet. Jambura Journal of Informatics, 2(1), 1-22.



  • There are currently no refbacks.

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