- Institution
- 서울특별시
- Department
- 도시교통실 교통지도과
ㅇ 불법주정차 무인단속 CCTV 및 자전거전용차로 무인단속 CCTV 성능개선
Programme 무인단속시스템 운영 효율화를 위한 성능개선
Amounts and period
- Budgeted amount
- 783,904,000 KRW
- 전년도예산액
- Present in the source but not extracted
- Change
- Not comparable
Changes are calculated only when both amounts are known in full. No percentage is calculated when the comparison amount is zero.
Programme hierarchy and share
The selected item’s share of each parent budget, calculated from amounts in the same source document.
A share is not calculated for missing or partial amounts, non-positive parent amounts, or an item amount greater than its parent.
-
Department 도시교통실 교통지도과 4,876,749,000 KRW16.1%
-
Policy 교통흐름 개선 4,779,218,000 KRW16.4%
-
Programme 교통지도 활동(주차장관리계정) 4,359,119,000 KRW18.0%
-
Project 무인단속시스템 운영 효율화를 위한 성능개선 1,443,268,000 KRW54.3%
-
Budget category 시설비및부대비 Present in the source but not extracted
-
Statistical item 시설비 1,440,668,000 KRW54.4%
-
Item ㅇ 불법주정차 무인단속 CCTV 및 자전거전용차로 무인단속 CCTV 성능개선 783,904,000 KRW
- Category–statistical code
- 401-01
- Group
- Not provided in source
Original description
ㅇ 불법주정차 무인단속 CCTV 및 자전거전용차로 무인단속 CCTV 성능개선 783,904,000원 = 783,904
Institution and programme names are shown as the original Korean source text.
Detailed budget items
4 itemsData source
-
Open source PDF
서울특별시 · FY2024 본예산 · 통합회계 · 659e289ad6ab84.48340710
Opens in a new window
- Page
- 55 / 56
- Document ID
doc_3ncbynv85fenz6j19v7qf150br- Source document status
- Available
- File type
- application/pdf
- File size
- 719.438 KiB
- Location inside the source
- Page 55 Row 15 Line 35 Column page_text
Source and reference
FY 2024 release No source record
- Fiscal year of record
- 2024
- Fetched from the source
- 2026-07-29 18:49
- Read and interpreted
- 2026-07-29 18:49
- Query snapshot refreshed
- 2026-09-02 03:23
- Item ID
bi_1h73mhzhssvt5zn09a3rrx5r6p- Address of this item
- /en/BudgetDetail/Item/bi_1h73mhzhssvt5zn09a3rrx5r6p
Related records
Similar budgets
Keyword “자전거전용차로” · classification 401-01
No items with the same classification were found among the candidates checked.
AI analysis report
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