Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
The Convergence of Ai, Iot, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications

The Convergence of Ai, Iot, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications

Kerrache, Chaker Abdelaziz
Lahby, Mohamed
Pathan, Al-Sakib Khan

Hardcover

Series: Control, Robotics and Sensors

Technology & EngineeringGeneral Computers

ISBN10: 1837242437
ISBN13: 9781837242436
Publisher: Institution of Engineering & Technology
Published: Aug 25 2026
Pages: 251
Weight: 1.16
Height: 0.63 Width: 6.14 Depth: 9.21
Language: English

AI and data-driven methods, particularly machine and deep learning models, have revolutionized image processing tasks such as object detection and segmentation, as well as inverse sensing tasks such as atmospheric condition monitoring. These models enable highly accurate predictions from large, labelled datasets. However, one of the key challenges with current AI systems is their opacity. While they deliver precise results, they often fail to provide clear insights into the underlying mechanisms driving these predictions. The lack of interpretability, especially in the context of sensing data, complicates the understanding of how internal features are represented and utilized. This issue is particularly pronounced in smart environment applications, where artificial intelligence techniques are increasingly employed, yet their internal workings remain largely opaque.

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