Artificiallyintelligent Imaging Ai2 Sensors How Intelligent Cmos Imaging Devices Can Benefit Photovoltaics

• doi: 10.1109/ICMSAO.2017.7934899
• title: Artificially-Intelligent Imaging (AI2) sensors: How intelligent CMOS imaging devices can benefit Photovoltaics?
• publisher: IEEE
• isbn: 978-1-5090-5455-8
• issn:
• rank: 1682
• access_type: LOCKED
• content_type: Conferences
• abstract: In the present paper, we present a new research bridge between two of the current hottest research branches in electrical engineering devices namely; CMOS imaging and Photovoltaics (PV). We start by showing the similarity between core areas of interest in each one namely the device, i.e. the photodiode and the difference between the two research areas. We conclude with an equation that depicts the central contribution of this paper demonstrating that any improvement at the device level made in CMOS imaging technology will inevitably and positively impact PV and visa-versa. Particularly, the suggested intelligent (bio-mimicked) photo-sensors can boost the solar energy conversion of their PV counterparts. This might not be possible in certain cases where fabrication technologies do not allow that and for that matter a non-disruptive change in the fabrication processes are necessary to take advantage of the new devices advancements. Finally, we present a futuristic solution based on the above pivotal idea opening a door for novel applications especially in battery-less biomedicals and wearables.
• article_number: 7934899
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7934899
• html_url: https://ieeexplore.ieee.org/document/7934899/
• abstract_url: https://ieeexplore.ieee.org/document/7934899/
• publication_title: 2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)
• conference_location: Sharjah, United Arab Emirates
• conference_dates: 4-6 April 2017
• publication_number: 7932296
• is_number: 7934840
• publication_year: 2017
• publication_date: 4-6 April 2017
• start_page: 1
• end_page: 5
• citing_paper_count: 1
• citing_patent_count: 0
• download_count: 340
• insert_date: 20170529
• index_terms:
  • ieee_terms:
    • Photodiodes
    • Photovoltaic systems
    • Photovoltaic cells
    • CMOS image sensors
  • author_terms:
    • Smart CMOS Imaging
    • Photovoltaics
    • photo-rod diodes
    • biomimetic intelligent devices
    • Artificially-intelligent devices
  • dynamic_index_terms:
    • Intelligence
    • Image Sensor
    • Camera Sensor
    • Complementary Metal–oxide–semiconductor Image
    • Complementary Metal Oxide Semiconductor Image
    • Fabrication Process
    • Energy Conversion
    • Photodiode
    • Solar Energy Conversion
    • Market Share
    • Market-based
    • Solar Cells
    • Ergogenic
    • Performance Enhancement
    • Quantum Efficiency
    • Energy Harvesting
    • Photocurrent
    • Electron Hole Pairs
    • Solar Photovoltaic
    • Solar PV
    • Incident Light Intensity
    • Conversion Gain
    • Complementary Metal Oxide Semiconductor Technology
    • Sensor Pixel
    • Crystalline Si
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5090-5455-8, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5090-5454-1, isbnType: New-2005
• authors:
  • Author Name: Fayçal Saffih
    Affiliation: Electrical Engineering Department, UAE University, Al Ain, UAE
    Author URL: https://ieeexplore.ieee.org/author/37698301900
    ID: 37698301900
    Order: 1
    Author Affiliations:
    • Electrical Engineering Department, UAE University, Al Ain, UAE

Image Sensor

• sensor_type: CMOS
• resolution: Not specified
• dynamic_range: Not explicitly mentioned
• pixel_size: Not specified
• dark_current: Not explicitly mentioned

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

• frame_rate: Not explicitly mentioned
• signal_to_noise_ratio: Not explicitly mentioned
• sensitivity: Not explicitly mentioned
• shutter_speed: Not explicitly mentioned
• power_consumption: Not explicitly mentioned
• noise: Not explicitly mentioned

Applications & Benefits

• cell_imaging: Used in a variety of applications including smartphones, medical devices, and automotive systems.
• benefits: Enable digital imaging with high performance metrics.

Supporting Organizations

• supported_by: Not specified

Manuscript Details

• publication_date: 4-6 April 2017

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

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