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Parking_​Intelligent_​System

Native KNIME 5.12 parking recommendation workflow converted from parking_demo (1).ipynb.

Native KNIME 5.12 parking recommendation workflow converted from parking_demo (1).ipynb.

Campus Parking Intelligent System

Native KNIME implementation of weighted multi-criteria ranking and strict rule-based parking selection.

1. Load and clean

Read the workflow-local CSV, normalize text, keep supported zones, and remove duplicate space IDs.

2. Request and explanation

Edit Request Parameters. One Expression node creates the complete explanation used by both algorithms.

3A. Weighted Multi-Criteria Scoring

Zone 30%, accessibility 25%, availability 20%, duration 15%, distance 10%. Each score remains visible, then results are ranked and limited to the top 3.

3B. Strict Rule-Based Filtering

Require zone, duration, accessibility and optional availability. Sort qualifying spaces by distance and keep top 3.

Important behavior preserved

Available only is a hard condition in the rule branch but only contributes 20% in the weighted branch, matching the notebook.

Read the workflow-local raw parking CSV.
CSV Reader
Trim and uppercase the parking-space identifier.
String Manipulation
Trim the zone and standardize capitalization.
String Manipulation
Normalize Yes/No availability values.
String Manipulation
Normalize Yes/No accessible-bay values.
String Manipulation
Drop the missing zone and retain the five supported campus zones.
Rule-based Row Filter
Keep the first record for each normalized space_id.
Duplicate Row Filter
20% criterion: current availability, or full credit when Any is selected.
Rule Engine
15% criterion: min(max_hours / requested_hours, 1).
Math Formula
30% criterion: requested zone match.
Rule Engine
25% criterion: accessibility need and accessible-bay reservation.
Rule Engine
Classify scores at the notebook cutoff of 0.70.
Rule Engine
Sort by score descending, then distance ascending.
Sorter
10% criterion: 1 - distance / maximum cleaned distance.
Math Formula
Weighted total, rounded to three decimal places like the notebook.
Math Formula
Present the top three weighted recommendations and their score components.
Column Filter
Broadcast the single maximum-distance value to every parking record.
Cross Joiner
Save weighted_top3.csv for verification and demonstration.
CSV Writer (deprecated)
Keep the first three weighted recommendations.
Row Filter
Calculate the maximum cleaned distance used by the notebook normalization formula.
GroupBy
Allow only validated request rows into the decision branches.
Rule-based Row Filter
Keep the nearest three strict rule matches.
Row Filter
Edit this one-row table to change the requested zone, accessibility need, duration, or availability mode.
Table Creator
Expression
Present the nearest three records that pass every strict rule.
Column Filter
Broadcast the one-row request parameters to every cleaned parking record.
Cross Joiner
Require zone, duration, accessibility and optional availability exactly as in rule_based().
Rule-based Row Filter
Apply the notebook duration and zone validation before scoring.
Rule Engine
Sort qualifying rule matches by nearest distance.
Sorter
Save rule_based_top3.csv for verification and demonstration.
CSV Writer (deprecated)

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: haruk
Created at: 2026-10-09
On NodePit since: 2026-10-12
Last update: 2026-10-13
Created with KNIME version: v5.12.0

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