An Internet of Things Ambient Light Monitoring System

Nowadays, the Internet of Things (IoT) technologies are ubiquitous and widely used to solve everyday challenges related to power usage consumption, environmental condition, automation, and many more. A scalable IoT-based ambient light monitoring system is designed to measure the ambient light intensity or illuminance of particular indoor areas, with an implementation in campus. This system is designed to measure the light measurement autonomously and continuously without human involvement. The end-users are able to access the real-time information of the collected data via internet through a cloud-based IoT platform with analytics capabilities. This system will provide significant benefits to the campus community in terms of creating a more conducive environment, increased productivity, and improved health condition. Furthermore, its implementation can be easily extended to other human spaces to create even greater benefits to society at large.

[1]  Maneesha V. Ramesh,et al.  Water quality monitoring and waste management using IoT , 2017, 2017 IEEE Global Humanitarian Technology Conference (GHTC).

[2]  Mariana Mocanu,et al.  Industrial WSN node extension and measurement systems for air, water and environmental monitoring: IoT enabled environment monitoring using NI WSN nodes , 2017, 2017 16th RoEduNet Conference: Networking in Education and Research (RoEduNet).

[3]  Hellen Adams,et al.  Patent and Trademark Office , 2017 .

[4]  Milan S. Matijevic,et al.  Overview of architectures with Arduino boards as building blocks for data acquisition and control systems , 2016, 2016 13th International Conference on Remote Engineering and Virtual Instrumentation (REV).

[5]  Ahmed Mohamed,et al.  Internet of things based smart environmental monitoring using the Raspberry-Pi computer , 2015, 2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC).

[6]  Neeraj Khera,et al.  Remote Condition Monitoring of Real-Time Light Intensity and Temperature Data , 2015, 2015 Second International Conference on Advances in Computing and Communication Engineering.

[7]  Wei-Jen Lee,et al.  Arc flash light intensity measurement system design , 2015, 2015 IEEE IAS Electrical Safety Workshop.

[8]  R. Ramya,et al.  The real time monitoring of water quality in IoT environment , 2015, 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS).

[9]  Bin Zhang,et al.  Air-kare: A Wi-Fi based, multi-sensor, real-time indoor air quality monitor , 2015, 2015 IEEE International Wireless Symposium (IWS 2015).

[10]  Chin-Chiuan Lin,et al.  Effect of Noise Intensity and Illumination Intensity on Visual Performance , 2014, Perceptual and motor skills.

[11]  Majid Hajibabaei,et al.  Comparison of Different Methods of Measuring Illuminance in the Indoor of Office and Educational Buildings , 2014 .

[12]  Jun Jiao,et al.  Design of Farm Environmental Monitoring System Based on the Internet of Things , 2014 .

[13]  Chung-Horng Lung,et al.  Smart Home: Integrating Internet of Things with Web Services and Cloud Computing , 2013, 2013 IEEE 5th International Conference on Cloud Computing Technology and Science.

[14]  Subhas Chandra Mukhopadhyay,et al.  Towards the Implementation of IoT for Environmental Condition Monitoring in Homes , 2013, IEEE Sensors Journal.

[15]  Huang Yong Research of Real-Time Optical Intensity Sensing System with Wireless Sensor Network , 2011, 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing.

[16]  Sarun Sumriddetchkajorn,et al.  Low-cost cell-phone-based digital lux meter , 2010, SPIE/COS Photonics Asia.

[17]  P. Oltman Field Dependence and Arousal , 1964, Perceptual and Motor Skills.