In industrial IoT projects, integrating LoRaWAN device data into existing PLC or SCADA systems has always been a major challenge. With ThinkLink’s native Modbus TCP support, wireless data can now be seamlessly integrated into industrial systems without complex development or architectural changes. 1. The Challenge of Integrating LoRaWAN with Industrial Systems Most industrial automation systems, […]

In LoRaWAN networks, time synchronization is not naturally guaranteed due to low-power and asynchronous communication. DeviceTimeReq is the mechanism designed to solve this challenge. 1. What is DeviceTimeReq? DeviceTimeReq is a MAC-layer command that allows end devices to request the current network time from the Network Server. The server responds with DeviceTimeAns. 👉 It provides

In large-scale LoRaWAN deployments, network congestion caused by limited downlink capacity has become a critical bottleneck. This article analyzes the root cause of air interface congestion and introduces three proven optimization strategies: join procedure control, confirmed message reduction, and local ADR implementation. These methods significantly improve network throughput and reliability. 1. Root Cause: Uplink–Downlink Asymmetry

Introduction: Why Weight Data Needs to Go Online In many industrial scenarios, weight data has always been critical. However, in traditional deployments, this data often remains local and isolated. With the rise of Industrial IoT, more applications now require: As a result, connecting weighing devices to IoT platforms has become essential. Typical Application Scenarios Weight

In LoRaWAN-based IoT systems, reducing power consumption while maintaining data accuracy is critical. The COV (Change of Value) algorithm enables event-driven communication by transmitting data only when significant changes occur. This article explains the working principle of COV and demonstrates how Manthink implements it in EdgeBus and ThinkLink to optimize energy efficiency and network scalability.

Battery life is a critical factor in wireless metering systems. This article analyzes the power consumption performance of the KC22 LoRaWAN collector based on real long-term testing in an M-Bus heat meter scenario. By comparing high-frequency test data with real deployment conditions, we estimate the practical battery life in heating applications. The article also demonstrates

1. Solution Overview In IoT deployments, low power consumption, long-range communication, and stable data acquisition are critical. This solution integrates: to build a complete wireless distance monitoring system. 2. DYP-A02 Sensor Features Feature Description Small blind zone Only 3 cm Multiple interfaces Modbus / UART / PWM / Analog წყალproof design Suitable for harsh environments

With the modernization of district heating systems, many older residential communities are upgrading traditional heat meters to smart metering systems. Manual meter reading is inefficient and lacks real-time monitoring capability. By combining LoRaWAN wireless communication, M-Bus data acquisition, and an IoT platform, heat meters can be remotely monitored without large-scale infrastructure reconstruction. This article introduces

With the rapid development of IoT technologies, LoRaWAN has become widely adopted in smart cities, industrial monitoring, environmental sensing, and energy management due to its long communication range, low power consumption, and wide coverage. However, during large-scale deployments, many projects encounter a puzzling issue after running for some time: the network signal appears strong, yet

For battery-powered IoT systems, DTU power consumption calculation plays a critical role in determining device lifetime and maintenance cost. Accurate power analysis helps engineers design proper battery capacity, optimize communication strategies, and extend device operation for years. This article explains the power consumption components of a LoRaWAN DTU, introduces calculation methods, and provides practical engineering