Modern smart meters are built on state-of-the-art technologies that ensure reliable and secure data transmission, while maintaining real-time control over meter availability. Although telemetry data is transmitted using the DLMS/COSEM protocol, true operational success would not be possible without the continuous supervision of network quality - and this is where LwM2M and Coiote IoT DM and Anjay IoT SDK play a crucial role.
Smart meters equipped with the Anjay LwM2M Client can be monitored in real time, enabling DSOs to verify availability, analyze behavior patterns, maintain fleet security, ensure future readiness through remote upgrades, and minimize connectivity loss. A meter that is offline cannot report consumption data. This leads to operational disruptions, service gaps, and increased costs. At scale, when managing millions of endpoints ensuring stable connectivity and enabling early detection of non-functioning devices becomes mission-critical. Even a single communication failure or data gap can disrupt energy balancing, delay billing, and compromise service quality.
Challenge Overview:
In large-scale smart metering deployments, maintaining reliable visibility into device status remains a persistent challenge - especially when devices go offline. Once connectivity is lost, operators are effectively blind to portions of their infrastructure. This loss of visibility is frequently due to external factors such as Cellular Radio Tower (BTS) issues, uncoordinated reconfigurations by mobile network operators, or suboptimal placement of meters - often in basements or other shielded environments where signal propagation is poor.
The operational consequences of this are significant. Offline devices not only fail to transmit critical usage data needed for accurate billing but also require costly manual interventions. Field service teams are often dispatched to diagnose issues that stem not from faulty hardware, but from avoidable connectivity problems. When scaled across millions of devices, these manual maintenance efforts represent a substantial operational burden.
Consider a real-world case: during monthly billing cycles, it was observed that between 4% and 7% of smart meters failed to report their measurements. In a deployment of one million smart meters, this equates to a staggering 40-70k missing data points every month - each representing a lost measurement critical for billing, analytics, and operational planning. The financial impact includes substantial manual meter reading costs, increased operational complexity, and the inability to support dynamic pricing models that depend on real-time data availability.
Business impact:
These challenges highlight the need for proactive, connectivity-aware device management strategies that can detect, adapt to, and mitigate the root causes of disconnection before they escalate into operational costs.
How Coiote IoT DM and Anjay IoT SDK Help:
Result:
Coiote IoT DM enables continuous oversight even during partial outages, ensuring that DSOs can detect anomalies early, recover data post-factum, and optimize operational workflows without manual diagnostics.
Challenge Overview:
When devices stop communicating for extended periods (for example, more than 3 days), it may be caused by physical disconnection, such as tampering or damaged wiring; SIM card or mobile network service issues; firmware crashes or device lockups. These silent failures create blind spots in the network and delay the detection and resolution of problems.
How Coiote IoT DM and Anjay IoT SDK Help:
Result:
With Coiote IoT DM and Anjay IoT SDK, DSOs can identify silent faults proactively, reduce mean time to repair, multiple service activities or on-site interventions ultimately ensuring better service continuity and lower maintenance costs.
Challenge Overview:
Frequent switching between mobile base stations (BTS) or changes in network frequencies is often symptomatic of deeper connectivity or configuration issues within the device's operating environment. This phenomenon may indicate underlying signal instability, where the radio conditions fluctuate rapidly due to environmental obstacles, poor antenna placement, or dynamic interference. In some cases, the root cause may lie in the overall network quality especially in areas with high device density or insufficient infrastructure coverage, which results in competition for available resources and degraded service continuity.
Additionally, improper configuration of the radio module on the device itself can exacerbate this problem. For instance, incorrect parameters related to preferred frequency bands, handover thresholds, or power-saving modes can cause the module to behave erratically, leading to unnecessary and frequent attempts to reselect or switch cells.
This unstable behavior can significantly impact device performance and system reliability. First, ongoing handovers and reattachments interrupt communication sessions, which is especially problematic for time-sensitive operations. Second, such instability increases the number of retransmissions, leading to higher data overhead.
But perhaps the most concerning is the potential failure in delivering critical commands to the device. In a device management scenario, operations such as remote firmware updates or device reconfigurations must be executed reliably. Frequent BTS or frequency switching can break the command pipeline, delay execution, or even result in total communication failure, undermining both operational efficiency and service-level agreements.
Understanding and addressing this challenge is vital for ensuring robust, predictable, and energy-efficient operation of IoT deployments, especially in utility-grade or mission-critical applications.
How Coiote IoT DM and Anjay IoT SDK Help:
Result:
Coiote IoT DM and Anjay IoT SDK empowers DSOs to fine-tune connectivity parameters, analyze mobility behavior, and reduce unnecessary radio activity - resulting in improved data reliability, device longevity, and smoother network operations.
Challenge Overview:
Low signal strength is one of the most pervasive and disruptive issues in wireless communication for IoT devices. When the received signal power falls below a certain threshold, the device’s ability to maintain a stable and efficient connection is compromised. This weak signal condition often occurs in environments where physical obstructions such as thick walls, underground installations (e.g., basements), or remote rural areas impede radio wave propagation. It may also stem from external interference, suboptimal antenna placement, or simply operating at the edge of cellular coverage.
As the signal weakens, the reliability of communication degrades. Devices begin to experience increased latency during data transmissions due to longer negotiation times and more frequent retries caused by failed packets.
Over time, if the signal conditions do not improve, the device may face complete communication loss, rendering it inaccessible for remote operations. This poses a serious risk in scenarios where devices are expected to perform critical functions, such as real-time monitoring, control signals, or alarm reporting. Compounding the issue, such weak signal conditions are often difficult to detect through standard monitoring, since they require direct diagnostics from the modem or radio module data that is not always readily available or visible in conventional dashboards.
Effectively addressing weak signal strength requires proactive radio diagnostics, careful placement planning, and in some cases, network-side support such as signal repeaters or optimized frequency use to maintain operational integrity in challenging locations.
How Coiote IoT DM and Anjay IoT SDK Help:
Result:
Thanks to Coiote IoT DM and Anjay IoT SDK, operators can monitor weak signal trends in real time, intervene before service disruption occurs, and make informed infrastructure and network decisions to prevent recurring issues.
As utilities across Europe and beyond respond to regulatory mandates and rising customer expectations, the road to a smarter, greener, and more resilient energy grid demands not only the right devices but also the right tools to manage them.
AVSystem’s Coiote IoT Device Management Platform empowers Distribution System Operators to operationalize this transition with confidence. By leveraging the LwM2M standard, Coiote IoT DM provides unmatched visibility, control, and scalability; helping energy companies detect issues before they escalate, maintain stable connectivity across millions of endpoints, and ensure the quality of data flowing into platforms like CSIRE.
From overcoming connectivity blind spots to simplifying diagnostics and streamlining operations, AVSystem’s solutions are purpose-built to support smart metering success at scale. Because when your infrastructure is visible, intelligent, and secure, you're not just meeting compliance - you’re shaping the future of energy.