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A Data-Driven Solution for Logistics Asset Tracking and Maintenance

Neuron Team
Nov 17, 2023
A Data-Driven Solution for Logistics Asset Tracking and Maintenance

Overview

Logistics companies need to ensure the efficiency and longevity of their assets such as vehicles, containers, equipment, and inventory. This can be achieved through logistics asset tracking and maintenance.

  • Asset tracking uses technologies like GPS, RFID, sensors, and connectivity solutions to gather data about where assets are, how they move, and the conditions around them. This data is sent to a central system for analysis.

  • Maintenance involves two main strategies. Preventive maintenance follows set schedules for routine inspections, servicing, and repairs. Predictive maintenance uses data analytics and machine learning to predict patterns and potential issues in asset performance.

EMQ provides a comprehensive data-driven solution for logistics asset management with capabilities to collect, transmit, and process data. This helps companies monitor their logistics assets in real time and gain useful information, leading to informed decisions for management and improved competitiveness.

Challenges

Managing and tracking assets in logistics operations can be complex due to various challenges.

  • Asset Visibility: Logistics companies often deal with a vast number of assets, including vehicles, containers, and inventory items, spread across multiple locations. Lack of real-time visibility into asset location and status can lead to inefficiencies, delays, and increased costs.
  • Asset Utilization: Logistics companies need to optimize asset utilization to reduce costs and improve efficiency by tracking asset availability, utilization rates, and usage patterns.
  • Maintenance Downtime: Unscheduled maintenance or breakdowns can disrupt logistics operations, causing delays, customer dissatisfaction, and increased expenses. Predicting and preventing asset failures through proactive maintenance practices is essential to minimize downtime and optimize asset performance.
  • Data Management: Logistics asset tracking generates vast amounts of data from various sources, such as GPS trackers, sensors, and maintenance records. Efficiently collecting, processing, and analyzing this data is crucial for gaining actionable insights, identifying patterns, and making data-driven decisions.
  • Connectivity and Interoperability: Logistics operations require seamless connectivity and interoperability between diverse devices, systems, and networks to ensure smooth data exchange and effective asset tracking.
  • Scalability and Cost: Companies need a cost-effective, scalable solution that can handle large volumes of data to accommodate future growth at minimal cost.

How EMQ Helps

Logistics Tracking

  • Scalability for Growing Assets: EMQX is designed to handle large-scale deployments and high message throughput. It offers horizontal scalability, allowing the system to expand seamlessly as the number of assets and data streams increases. This scalability ensures that logistics companies can effectively track and manage growing assets without compromising system performance or reliability.
  • Connectivity for Comprehensive Elements with Multi-Protocol Support: At the edge, the industrial gateway NeuronEX provides the mainstream industrial protocol access capability. In the cloud, EMQX's robust implementation of the MQTT protocol ensures efficient and reliable communication between assets, sensors, and backend systems.
  • Derive Insights through Data Integration and Processing: EMQX enables real-time data processing at the edge or in the cloud. It supports integration with all kinds of popular data persistence and analytics platforms and tools, allowing logistics companies to derive meaningful insights from the collected asset data. This enables predictive maintenance capabilities, anomaly detection, and asset performance optimization based on data-driven decision-making.
  • Remote Monitoring and Control: Logistics companies can access and manage assets remotely, retrieve real-time data, and issue commands or configurations through EMQX. This capability is particularly valuable for geographically dispersed assets or assets in challenging environments with limited physical access.
  • Security Guarantee for Sensitive Information: EMQX offers robust security features such as authentication, encryption, and access control, ensuring that only authorized entities can access and interact with asset data. This helps protect sensitive information, prevent unauthorized access, and maintain the integrity of the logistics asset tracking and maintenance system.

EMQX Enterprise

EMQX Enterprise is a powerful enterprise-level IoT messaging platform designed for large-scale deployments and high reliability in IoT applications. The following capabilities of EMQX Enterprise can benefit the industry:

  • High Reliability and Scalability: EMQX Enterprise adopts a distributed architecture with high availability and scalability to handle large-scale concurrent message transmission. It supports horizontal scaling to accommodate the growing number of IoT devices and data traffic, ensuring system stability.
  • Rich Protocol Support: EMQX Enterprise supports multiple messaging protocols besides the MQTT protocol. It allows developers to extend to support all kinds of private protocols for their application needs.
  • Data Integration: EMQX Enterprise seamlessly integrates with various data storage services, message queues, cloud platforms, and applications. It can connect with cloud services, enabling remote data transmission and cloud-based analysis.
  • Security and Authentication: EMQX Enterprise provides robust security features, including TLS/SSL encrypted transmission, client authentication, and access control. It supports various authentication methods such as username/password, X.509 certificates, and OAuth, ensuring the security of IoT communication.
  • Rule Engine and Data Processing: EMQX Enterprise has a flexible rule engine for real-time data processing and forwarding based on device data. It supports operations such as data filtering, transformation, aggregation, and persistence, helping users analyze and make decisions based on their business needs.
  • Visual Monitoring and Management: EMQX Enterprise provides an intuitive visual monitoring and management interface, allowing users to monitor IoT devices and message transmission in real-time. Users can view connection status, message traffic, and other metrics and perform device management, troubleshooting, and system configuration operations.

NeuronEX

NeuronEX is software tailored for the industrial sector, focusing on equipment data collection and edge intelligent analysis. It is primarily deployed in industrial settings, facilitating industrial equipment communication, industrial bus protocol acquisition, industrial system data integration, edge-level data filtering and analysis, AI algorithm integration, and integration with IIOT platforms. It offers the following features:

  • Diverse Connectivity: NeuronEX provides multi-protocol access capability, supporting simultaneous access to dozens of industrial protocols such as Modbus, OPC UA, Ethernet/IP, BACnet, Siemens, Mitsubishi, and more. It enables integration with multiple data sources from systems like MES and WMS within the enterprise. NeuronEX also supports bidirectional data flow, allowing both data acquisition and control command issuance to devices.
  • Deploy anywhere: NeuronEX has very low memory footprints and is suitable for running on low-profile architecture devices like x86, ARM, RISC-V, etc. It also supports docker-like containerized deployment, running with other co-located containers in Kubernetes environments.
  • Data Processing: NeuronEX incorporates 100+ built-in functions, supporting data filtering, data manipulation, device control, and data persistence, storing data in a time-series database.
  • Algorithm Integration: NeuronEX supports the integration of algorithms written in languages such as C, Python, and Go. It facilitates real-time inference of industrial mechanism models, machine learning, and deep learning models at the edge, enabling alerts and intelligent decision-making.
  • Edge to Cloud: Through protocols like MQTT and SparkplugB, NeuronEX aggregates and pushes industrial data to cloud platforms. The bidirectional data flow between NeuronEX and the cloud platform establishes cloud-edge data coordination and control synergy, leveraging the platform's big data storage and analysis capabilities to amplify the value of NeuronEX usage.

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