diff --git a/src/algorithm/bellande_node_importance.rs b/src/algorithm/bellande_node_importance.rs
index 68a0a2d..c6eed34 100644
--- a/src/algorithm/bellande_node_importance.rs
+++ b/src/algorithm/bellande_node_importance.rs
@@ -13,5 +13,292 @@
 // You should have received a copy of the GNU General Public License
 // along with this program.  If not, see <https://www.gnu.org/licenses/>.
 
-use crate::algorithm::connections::BellandeArchError;
+use crate::algorithm::connections::{euclidean_distance, BellandeArchError};
 use bellande_node_importance::make_bellande_node_importance_request;
+use futures::future::join_all;
+use serde::{Deserialize, Serialize};
+use serde_json::Value;
+
+/// Configuration for node importance evaluation using Bellande Node Importance algorithm
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct NodeImportanceConfig {
+    pub node_coordinates: Vec<f64>,
+    pub segment_id: String,
+    pub recent_nodes: Vec<Vec<f64>>,
+    pub important_nodes_by_segment: std::collections::HashMap<String, Vec<Vec<f64>>>,
+    pub adjacent_segments: std::collections::HashMap<String, Vec<String>>,
+    pub grid_steps: Vec<f64>,
+    pub min_segment_coverage: f64,
+    pub use_local_executable: bool,
+}
+
+/// Result of a node importance evaluation operation
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct NodeImportanceResult {
+    pub importance_score: f64,
+    pub coverage_metrics: Option<Vec<f64>>,
+    pub segment_coverage: Option<f64>,
+    pub execution_time_ms: Option<i32>,
+    pub node_attributes: Option<std::collections::HashMap<String, Value>>,
+}
+
+/// Extended configuration for advanced node importance evaluations
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct AdvancedNodeImportanceConfig {
+    pub basic_config: NodeImportanceConfig,
+    pub priority_regions: Option<Vec<Vec<Vec<f64>>>>,
+    pub coverage_bias: Option<f64>,
+    pub weighting_factor: Option<f64>,
+}
+
+/// Main node importance evaluation module that leverages the Bellande Node Importance algorithm
+pub struct NodeImportanceEvaluator;
+
+impl NodeImportanceEvaluator {
+    /// Evaluates the importance of a node using the Bellande Node Importance algorithm
+    pub async fn evaluate(
+        config: NodeImportanceConfig,
+    ) -> Result<NodeImportanceResult, BellandeArchError> {
+        // Validate input coordinates
+        if config.node_coordinates.is_empty() {
+            return Err(BellandeArchError::InvalidCoordinates(
+                "Node coordinates cannot be empty".to_string(),
+            ));
+        }
+
+        // Validate segment ID
+        if config.segment_id.is_empty() {
+            return Err(BellandeArchError::InvalidCoordinates(
+                "Segment ID cannot be empty".to_string(),
+            ));
+        }
+
+        // Validate grid steps
+        if config.grid_steps.is_empty() {
+            return Err(BellandeArchError::InvalidCoordinates(
+                "Grid steps cannot be empty".to_string(),
+            ));
+        }
+
+        let dimensions = config.node_coordinates.len();
+
+        // Verify that grid steps have the same dimensions as node coordinates
+        if dimensions != config.grid_steps.len() {
+            return Err(BellandeArchError::DimensionMismatch(format!(
+                "Coordinate dimension mismatch: node={}, grid_steps={}",
+                dimensions,
+                config.grid_steps.len()
+            )));
+        }
+
+        // Create the node JSON structure
+        let node = serde_json::json!({
+            "coords": config.node_coordinates,
+            "segment": config.segment_id
+        });
+
+        // Convert recent nodes to JSON Value
+        let recent_nodes = serde_json::json!(config.recent_nodes);
+
+        // Convert important nodes to JSON Value
+        let important_nodes = serde_json::json!(config.important_nodes_by_segment);
+
+        // Convert adjacent segments to JSON Value
+        let adjacent_segments = serde_json::json!(config.adjacent_segments);
+
+        // Convert grid steps to JSON Value
+        let grid_steps = serde_json::json!(config.grid_steps);
+
+        // Run the Bellande Node Importance algorithm using the API
+        let result = if !config.use_local_executable {
+            make_bellande_node_importance_request(
+                node,
+                recent_nodes,
+                important_nodes,
+                adjacent_segments,
+                grid_steps,
+                config.min_segment_coverage,
+            )
+            .await
+            .map_err(|e| BellandeArchError::AlgorithmError(e.to_string()))?
+        } else {
+            return Err(BellandeArchError::AlgorithmError(
+                "Local executable functionality not implemented".to_string(),
+            ));
+        };
+
+        // Process and transform the results
+        Self::process_result(result)
+    }
+
+    /// Process the raw Bellande Node Importance result into our domain-specific format
+    pub fn process_result(result: Value) -> Result<NodeImportanceResult, BellandeArchError> {
+        // Extract the importance score from the result
+        let importance_score = result
+            .get("importance_score")
+            .and_then(|s| s.as_f64())
+            .ok_or_else(|| {
+                BellandeArchError::AlgorithmError(
+                    "Missing importance score in algorithm result".to_string(),
+                )
+            })?;
+
+        // Extract coverage metrics if available
+        let coverage_metrics = result
+            .get("coverage_metrics")
+            .and_then(|m| m.as_array())
+            .map(|metrics| {
+                metrics
+                    .iter()
+                    .filter_map(|v| v.as_f64())
+                    .collect::<Vec<f64>>()
+            });
+
+        // Extract segment coverage if available
+        let segment_coverage = result.get("segment_coverage").and_then(|c| c.as_f64());
+
+        // Extract execution time if available
+        let execution_time_ms = result
+            .get("execution_time_ms")
+            .and_then(|t| t.as_i64())
+            .map(|t| t as i32);
+
+        // Extract node attributes if available
+        let node_attributes = result
+            .get("node_attributes")
+            .and_then(|a| a.as_object())
+            .map(|obj| {
+                obj.iter()
+                    .map(|(k, v)| (k.clone(), v.clone()))
+                    .collect::<std::collections::HashMap<String, Value>>()
+            });
+
+        Ok(NodeImportanceResult {
+            importance_score,
+            coverage_metrics,
+            segment_coverage,
+            execution_time_ms,
+            node_attributes,
+        })
+    }
+
+    /// Evaluates node importance with optimal parameters based on segment characteristics
+    pub async fn evaluate_optimal(
+        node_coords: Vec<f64>,
+        segment_id: String,
+        recent_nodes: Vec<Vec<f64>>,
+        important_nodes_by_segment: std::collections::HashMap<String, Vec<Vec<f64>>>,
+        adjacent_segments: std::collections::HashMap<String, Vec<String>>,
+    ) -> Result<NodeImportanceResult, BellandeArchError> {
+        // Validate inputs
+        if node_coords.is_empty() || segment_id.is_empty() {
+            return Err(BellandeArchError::InvalidCoordinates(
+                "Node coordinates and segment ID cannot be empty".to_string(),
+            ));
+        }
+
+        let dimensions = node_coords.len();
+
+        // Determine appropriate grid steps based on segment characteristics
+        let grid_steps = if let Some(segment_nodes) = important_nodes_by_segment.get(&segment_id) {
+            if !segment_nodes.is_empty() {
+                // Calculate average distance between nodes in this segment
+                let mut total_distance = 0.0;
+                let mut count = 0;
+
+                for i in 0..segment_nodes.len() {
+                    for j in i + 1..segment_nodes.len() {
+                        if let Ok(dist) = euclidean_distance(&segment_nodes[i], &segment_nodes[j]) {
+                            total_distance += dist;
+                            count += 1;
+                        }
+                    }
+                }
+
+                let avg_distance = if count > 0 {
+                    total_distance / count as f64
+                } else {
+                    1.0
+                };
+                // Use 10% of average distance as grid step
+                vec![avg_distance * 0.1; dimensions]
+            } else {
+                // Default grid steps if no nodes in segment
+                vec![1.0; dimensions]
+            }
+        } else {
+            // Default grid steps if segment not found
+            vec![1.0; dimensions]
+        };
+
+        // Determine minimum segment coverage based on adjacent segments count
+        let adjacent_count = adjacent_segments
+            .get(&segment_id)
+            .map(|adj| adj.len())
+            .unwrap_or(0);
+
+        let min_segment_coverage = match adjacent_count {
+            0 => 0.7,     // Isolated segment, require higher coverage
+            1..=2 => 0.6, // Few connections
+            3..=5 => 0.5, // Moderate connections
+            _ => 0.4,     // Many connections, can be more flexible
+        };
+
+        // Basic configuration
+        let config = NodeImportanceConfig {
+            node_coordinates: node_coords,
+            segment_id,
+            recent_nodes,
+            important_nodes_by_segment,
+            adjacent_segments,
+            grid_steps,
+            min_segment_coverage,
+            use_local_executable: false,
+        };
+
+        // Perform evaluation
+        Self::evaluate(config).await
+    }
+
+    /// Batch processes multiple node importance evaluations in parallel
+    pub async fn batch_evaluate(
+        configs: Vec<NodeImportanceConfig>,
+    ) -> Vec<Result<NodeImportanceResult, BellandeArchError>> {
+        // Process each configuration in parallel
+        let futures = configs.into_iter().map(|config| Self::evaluate(config));
+
+        // Collect all results
+        join_all(futures).await
+    }
+
+    /// Advanced batch processing with custom parameters for each evaluation
+    pub async fn advanced_batch_evaluate(
+        configs: Vec<AdvancedNodeImportanceConfig>,
+    ) -> Vec<Result<NodeImportanceResult, BellandeArchError>> {
+        let futures = configs.into_iter().map(|config| {
+            // Use basic evaluation
+            Self::evaluate(config.basic_config)
+        });
+
+        join_all(futures).await
+    }
+
+    /// Calculates a comparative importance score between two nodes
+    pub fn calculate_comparative_importance(
+        node1_result: &NodeImportanceResult,
+        node2_result: &NodeImportanceResult,
+        weighting_factor: f64,
+    ) -> f64 {
+        // Basic comparison of importance scores
+        let importance_diff = node1_result.importance_score - node2_result.importance_score;
+
+        // Consider segment coverage if available
+        let coverage_factor = match (node1_result.segment_coverage, node2_result.segment_coverage) {
+            (Some(cov1), Some(cov2)) => (cov1 - cov2) * weighting_factor,
+            _ => 0.0,
+        };
+
+        // Combined score
+        importance_diff + coverage_factor
+    }
+}
diff --git a/src/algorithm/bellande_step.rs b/src/algorithm/bellande_step.rs
index d36df90..ca286eb 100644
--- a/src/algorithm/bellande_step.rs
+++ b/src/algorithm/bellande_step.rs
@@ -14,8 +14,7 @@
 // along with this program.  If not, see <https://www.gnu.org/licenses/>.
 
 use crate::algorithm::connections::{
-    euclidean_distance, is_point_valid, vector_dot_product, vector_length, vector_subtract,
-    BellandeArchError,
+    euclidean_distance, vector_dot_product, vector_length, vector_subtract, BellandeArchError,
 };
 use bellande_step::make_bellande_step_request;
 use futures::future::join_all;