M. Ahmed Khan
FAST
· 2022
·
i22 - 2200
Email
—
Phone
—
LinkedIn
—
GitHub
—
Academic
Program
FAST NUCES ISLAMABAD CAMPUS
CGPA
—
Year
2022
Education
FAST NUCES ISLAMABAD CAMPUS
Address
—
DOB
—
Career
Current role
—
Target role
—
Skills
Computer Vision, Object Detection, Structural Recognition, Geospatial Intelligence (GIS), Drone Technology, Aerial Data Acquisition
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
Automated Map Change and Encroachment Detection System using Computer Vision apid urbanization and unplanned development have significantly increased the risk of illegal onstructions and land encroachments, especially in developing regions. Traditional land monitoring ethods rely heavily on manual surveys, physical inspections which are time-consuming and often ·nefficient. To address these challenges, this project proposes an intelligent, automated land onitoring system that integrates drone-based imaging, computer vision, and geospatial analysis for ·eal-time detection of map changes and encroachments. he proposed system utilizes a drone equipped with a high-resolution camera and GPS module to apture real-time aerial imagery of targeted regions such as housing societies, construction sites, and gricultural zones. The captured images are geo-referenced and processed using computer vision echniques to detect stmctural patterns and land-use changes. These images are then compared agains fficial layout plans and digital map data from platforms such as OpenStreetMap (OSM) to identify hanges between approved plans and actual ground conditions. y implementing automated change detection algo1ithms, the system can highlight new constructions r structural modifications that deviate from authorized maps. The detected anomalies are visually arked and displayed on screen, allowing authorities, urban planners, and land administrators to easily monitor and verify. An Automated Map Change and Encroachment Detection System using Computer Vision ObJoctlv• :Autoc:vt• G1 lecboti of u~Uthotulld fArtd c:h:.ngn l'\O encro c:nment lhfOtt&h drone-ba$ed $1Jtvflll:i'nce $Y'$tem vulll !'I& compuw v,sfon end GPS techllO ology Atf•r 122·21.SM :Ahmed Kh.1n 122·2200 Muli.&fa Slwfqaar 122-985S AppUutJoiis U<bt.n P1ann•111 MIi Sm¥t cmes · ll- u_· • tfl 1llecat£nctotehmentden:ctlon d'ti) - _ · t.811(1 a.no Propeny Mana,emen, - - Technology Used: Computer Vision for object detection and stmctural recognition Geospatial Intelligence (GIS) for spatial data ignment and map comparison Drone Technology for aerial data acquisition Supervisor Name: Dr. Shahzad Saleem Group Members: M. lshtiaq Azfar (i22 - 2194) M. Ahmed Khan (i22 - 2200) Mustafa Shafqaat (i22 - 9855) FAST NUCES ISLAMABAD CAMPUS
Provenance
Source file: FAST School of Engineering - Graduate Directory 2026.pdfFrom job #392 page 59
Created: 1778490552