Logistics

• Warehouse Management functionality development (stock tracking, order management)
• Indoor mapping solutions for warehouses (mapping and optimizing storage space, optimal item placement suggestions)
• Automated Inspection and Quality Assurance (AI-Powered Vision Systems, UAV-based systems, IoT and RFID/Barcode-based monitoring solutions
• Warehouse Automation Systems (equipment integration, predictive maintenance)
• Warehouse security solutions (UAV-based systems, CCTV cameras processing)
• Third-Party Logistics (3PL) Integration
• Last-Mile Delivery Optimization

• Develop order picking, packing, and shipping workflows.
• Use algorithms to prioritize orders based on SLAs.
• Implement space optimization algorithms based on item demand and size.
• Develop APIs to connect warehouse robots, conveyor belts, and sorting systems.
• Use EDI for order and shipment data synchronization.

• Inventory
• Order
• Shipment
• Transactional
• Indoor spatial
• Sensor
• Equipment
• Workflow
• Security logs

• EDI (Electronic Data Interchange)
• Websocket
• MQTT
• ROS
• Profinet
• Modbus
• RTSP
• Webhooks

• Django/Flask, React/Angular, Pandas/Numpy
• OpenCV
• Mapbox, Leaflet
• DroneKit
• Simulink/Matplotlib
• PyEDIFACT

• Environmental Condition Monitoring and related risk management
• Data transfer, storage and analysis solutions (on board if the truck and cloud-based)
• Driver decision making assistance solutions
• Integration with ERP and TMS Systems

• Edge computing
• AI-driven anomaly detection
• Data compression & optimization:
• Event-driven architecture

• Temperature, humidity, pressure, vibration, and GPS location.
• Event logs (e.g., door open/close events, temperature deviations).
• GPS data, fuel consumption, engine health, driver behavior metrics, cargo condition data.
• Video telemetry (dashcams, ADAS systems).

• LoRaWAN
• Bluetooth Low Energy (BLE)
• Cellular (4G/5G), Wi-Fi, and Satellite
• CAN bus (Controller Area Network)
• V2X (Vehicle-to-Everything)
• LTE-M / NB-IoT
• Apache Kafka / MQTT / AMQP

• AWS IoT Core / Azure IoT Hub
• Apache Spark / Databricks
• InfluxDB / TimescaleDB
• OpenCV / YOLO
• PyTorch / TensorFlow

• Real-Time Fleet Monitoring & Management
• Freight & Dock Dynamic Scheduling (based on priorities, queue information and real-time vehicle location)
• Driver Behavior Analysis & Safety Monitoring (data analytics, scoring and gamification systems)
• Custom solutions for environmental parameters-sensitive logistics (Temperature, light, dust, humidity, etc.
• Predictive Maintenance & Vehicle Health Monitoring

GPS Data Processing & Route

• Kalman Filter,
• Hidden Markov Models,
• Dijkstra’s Algorithm,
• Recurrent Neural Networks

IoT Sensor Fusion & Telemetry Processing

• Bayesian Sensor Fusion
• Fourier Transform / Wavelet Analysis
• Statistical Process Control (SPC) & Z-Score Analysis

Traffic Prediction & ETA Calculation

• Graph Neural Networks (GNNs) / Spatio-Temporal Graph Convolutional Networks (ST-GCNs)
• ARIMA (AutoRegressive Integrated Moving Average)
• Monte Carlo Simulation

Data Fusion Strategy

• Multi-Modal Sensor Fusion
• AI-based Anomaly Detection
• Edge AI

AI-Based Scheduling & Optimization

• Constraint Satisfaction Problem (CSP) Solvers (Google OR-Tools, OptaPlanner)
• Hungarian Algorithm / Kuhn-Munkres Algorithm
• Genetic Algorithms
• Queueing Theory (M/M/1, M/M/c Models)

Event Detection & Anomaly Analysis

• Autoencoders / Isolation Forests
• Dynamic Time Warping (DTW)
• Computer Vision
• LSTMs / GRUs (Gated Recurrent Units)

• Location Data
• Telemetry Data
• Traffic Data
• Environmental Data
• Driver Input
• Incident Reports
• IoT Sensor Data
• InfluxDB / TimescaleDB

• EDI (Electronic Data Interchange)
• Websocket
• MQTT
• ROS
• Profinet
• Modbus
• RTSP
• Webhooks

• OpenTelemetry
• Apache Kafka / RabbitMQ
• Grafana / Power BI
• Azure IoT Hub
• OpenCV / TensorFlow Lite

• POI Data Collection and validation
• Ground truth teams creation around the world
• Automated remote attribute data collection and measurement
• API development for the realtime data control on POI (queue, processing time, alerts/incidents reporting, weather related information
• AI-based prediction models development for POI-intelligence

• Crowdsourced Data Collection
• Web Scraping & Open Data Sources analytics
• Call-centers for POI validation
• Time-Series Forecasting for POI Activity.
• Anomaly Detection for Operational Efficiency.

POI types

• Warehouses & Distribution Centers
• Manufacturing & Industrial Facilities
• Freight Terminals & Depots
• Customs & Border Checkpoints
• Toll Booths & Weigh Stations
• Gas Stations & EV Charging Stations
• Rest Areas & Driver Facilities

Data types

• Geospatial Data
• Operational Data
• Real-time data
• Regulatory Data
• Incident & Weather Alerts
• Live Queue & Processing Times
• Historical POI Usage Data

• Geospatial Analysis: GDAL, GeoPandas, PostGIS
• Data Collection & Processing: Scrapy, Selenium, BeautifulSoup (for scraping), Pandas, Apache Spark
• Real-Time Data Streaming: Apache Kafka, Flink
• Mobile SDKs
• Data Sync & Storage: Firebase, AWS S3, SQLite for offline data collection.
• Computer Vision: OpenCV, TensorFlow, YOLO
• Big Data Processing: Apache Spark, Google BigQuery.
• Prediction modeling: TensorFlow, PyTorch, Scikit-learn.

• Custom Digital Document Management Systems development
• Electronic Bill of Lading (eBOL) & Digital Invoicing Solutions
• Automated Customs & Compliance Document Processing
• AI & OCR-Based Document Scanning & Digitization
• API & EDI Development for Document Exchange

• Cloud-based/On-premise-based solutions
• Auto-triggered invoice generation.
• AI-Based Document Classification
• Secure EDI for Data Exchange
• Automated Workflow Routing
• Real-Time API-Based Document Sharing.
• EDI for Large-Scale Business Transactions

• Structured Data: Metadata, shipment details, timestamps.
• Unstructured Data: PDFs, scanned images, emails, contracts.
• eBOL Fields: Shipper, consignee, carrier, cargo description.
• Invoice Data: Amounts, taxes, payment terms.
• EDI-Based Data Formats: X12, EDIFACT, UBL.
• Customs Declarations: HS codes, duties, taxes.

• EDI (X12, EDIFACT) via AS2, FTP, VANs.
• GraphQL APIs for Structured Data Retrieval
• Secure Transactions: AES-256 encryption, TLS 1.3.

• Document Storage: MongoDB GridFS, AWS S3, MinIO.
• E-Invoicing APIs: Peppol, Stripe API
• AI/NLP Processing: SpaCy, Transformers (BERT).
• OCR & Document Processing: Tesseract, OpenCV.
• EDI Mapping Tools: Altova MapForce, MuleSoft.
• ML Models for NLP: TensorFlow, PyTorch.

• AI-Powered Route Optimization Solutions
• Custom GPS Tracking & Fleet Navigation Systems
• Indoor Navigation & Warehouse Positioning Systems
• AI-Based Traffic Prediction & Congestion Avoidance Systems
• Graph-based solutions for intermodal transportation path planning and update
• Last-Mile Delivery Navigation & Optimization

• Real-time AI-based Routing
• Multi-stop Optimization
• Dynamic Re-Routing
• Real-time Fleet Tracking/Geofencing
• RTLS (Real-Time Location Systems)
• AR Navigation for Workers
• Multi-Modal Graph Modeling
• Smart Parcel Lockers & Drone Integration

• GPS Data
• POI Data
• Traffic & Incident Reports
• Weather Data:
• Historical Route Data
• Telematics Data/Event logs
• Warehouse Layout Maps
• Transport Network Graphs
• Customer Notifications & ETA Updates.

• Route Optimization: OR-Tools, GraphHopper, PgRouting.
• AI/ML Models: Scikit-Learn, XGBoost, TensorFlow.
• Mapping APIs: OpenStreetMap, Mapbox.
• Cloud Computing: AWS Lambda, Azure ML
• GPS Tracking: OpenGTS, Traccar.
• Indoor Mapping: HERE Indoor SDK, ArcGIS.
• RTLS & Positioning: OpenRTLS, Pozyx.
• Time-Series Forecasting: Prophet, LSTMs.
• Graph Databases: Neo4j, ArangoDB.
• AI-Powered Dispatching: OR-Tools, PyTorch