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IoT Platform for Water Infrastructure Management and Smart Metering

More generally, IoT is the broadest sense of terms, that looks like a network of devices or sensors that are connected to the internet. This technology finds application in various aspects of human life. It plays a main role as a technology factor for digital transformation.

When it comes to the journey of IoT, data collection and management is one of the challenging tasks. It imposes the following changes to the business field:

  • It certainly increases the wealth of the data transforming the added value for the data-driven business.
  • This lay a path to create opportunities for new services in the means of an asset, real-time acquisition, and monitoring of data and Artificial Intelligence (AI).

The IoT has helped several businesses in customer and operational data acquisition. These data were further used in the analysis, maintenance, and enhancing comfort in operational efficiency.

Tele-Measurement or Smart Metering is one of the major domains in the field of the Internet of Things (IoT). Smart metering has a diverse range of applications based on circumstance and place. It is a believed fact that the advanced metering infrastructure (AMI) leads to a reduction in the cost and demand to serve customers with improved communication. It finds its application in the public buildings, urban redevelopment, parking lots, terrestrial transport, hydraulic engineering, energy consumption, etc., The expansion of the smart metering in large scale leads to the integration of IoT platform that is capable of enhancing the data collected through the sensors. This integration of IoT improves operations, quality, and ensure service continuity. When it comes to smart metering in the distribution network AMIs play a vital role not only in distribution but also essential for surveillance, monitoring, and control the distribution and consumption level. A key factor that influences the AMI is the communication between the meters and the utility servers. The benefits and use cases of applying centralised IoT platform include:

  1. IoT plays a predictive role in extraordinary maintenance.
  2. It enrolls the calendar-based strategy to keep the devices and sensors in shape.
  3. An efficient way of data acquisition for analytics and adoption of AI tools.
  4. Capacity control in a distribution network.
  5. Centralized monitoring and critical event detection.

The sensors and the devices that are geographically dispersed should need a communication infrastructure as a core requirement. In addition to the different applications and benefits, the IoT platform itself should be designed in such a way that in future evaluation it should be able to integrate the extended architecture or use cases for data acquisition.

  • Analysis of data from the sensors and devices at the water distribution line, to find any wastage/leak using acoustic devices, temperature, and pressure in the water distribution network.
  • Processing of diverse data from sensors in the field of the residential system e.g. elevator, surveillance system, parking lot, environmental controls, etc.
  • Access control at various places like workplace, home, public gatherings, etc.
  • Water quality monitoring using sensor data for the drinking water management.

The water supply management using the smart technology powered by IoT is not only limited to the single application. These may be applied across various sectors such as mentioned above. When integrating such technology, data collection, and data analysis are used across sectors like water/wastewater management, transport, energy, buildings, security, communication, and environment management.

Architecture of the IoT platform in smart metering:

To implement the agile way of monitoring and management of the water distribution system the multi-layer system with the various industrial protocols is needed to integrate into the central system. The system can be simplified into a four-layer IoT reference model. The distributed devices or sensors installed on the field constitute the base physical layer of the reference model. The acquired data are transmitted through the secure communication protocol (TCP/IP, gateway device, etc.) to the remote server. The remote server provides the data to the management layer for the further process and analysis of the application needs.

Central Unit:

The data transmitted from the physical layer is received at the Central Unit (CU), which performs the analytical and control operations. The CU represents the IoT management layer where functionalities can be implemented such as optimization, data management, etc.

The online data received by the gateway are processed by the application layer algorithm, which identifies hidden patterns and analyzes the data based on their application. The algorithm correlates historical and real-time information to forecast the events.

Through the online monitoring of the available parameters, the prediction and optimization algorithms perform necessary action in a case of new occurred or anticipated events. While the data are stored in the Central Storage Unit to prevent possible data loss.

The basic technical requirement and application for the IoT platform and smart metering are:

  • Centralized data acquisition modules from the physical layer
  • Data collection, processing, and analytics
  • Device and sensor management in the field
  • Data management
  • Network analytics
  • Highly secure communication
  • Open-source platform
  • Integration and scalability of application in future
  • Industrial communication protocols
  • Access management module (IAM)
  • AI functionality
  • Real-time billing data

The system is designed in such a way that it could adapt to the increase in the new volumes to be managed. It should be capable of extending its count in the field sensors and system payload. When it comes to the technical stacks it should be able to manage the continuous update, centralized version control, and updated operating safety.

The role of Image processing and Artificial Intelligence:

Water supply equipment has a number of missed data that are not captured by the monitoring and the control system. For a well maintained and the better services these data also play a main role. It is also rare or impossible to capture all the data from the field without missing.

In order to make an autonomous system that collects all the need analogous data, an image-based solution plays a crucial role. For a case consider water pipelines with several analog-digital meters, with the image data of the meter can be processed and converted into the numeric reading.

Consider a thermal imaging system that plays the main role in temperature, leakage and loss prediction. These kinds of image data highly cut off the data transmission rate from several hundreds of data points to a single image.

Communication Protocols:

When it comes to the smart metering system for water management two-way communication is an important function. There are different communication protocols followed between the field sensors and central management systems and between consumer and the supplier. The different communication protocols have been defined and compared in terms of data-rate, frequency, coverage range, stability, and cost.

TechnologyCostCommunication modeFrequencyCoverage rangeLimitation
GPRSMediumStable900 -1800Mhz1-10KmData rates low
3GHighStable1.92Ghz – 1.98Ghz, 2.11-2.17Ghz1-10kmSpectrum costly
GSMLowStable900-1800Mhz1-10kmData rates low
WiFi-MaxMediumStable2.5-3.5Ghz10-50kmNot widespread
PLCLowVery Stable1-30Mhz1-3kmNoisy channel
SCADAHighStableUp to 1.54MhzShort distanceExpensive
M-BusHighLess Stable2.4-4.8Mhz1000mExpensive
ZigBeeMediumLess Stable2.4Ghz,868-915Mhz30-50mShort range
SigfoxMediumStable868 to 869 MHz10km (Urban) and 40km (rural)Restricted payload
LoRaMediumStableS, T, C modes (868 MHz) and N mode (169 MHz)5 kmLine of sight communication
WirelessHARTLessStable2.4 GHz225munsafe encryption

4G/5G:

As IoT is growing seamlessly there is a need for a technology that supports large amount of data transmission at very high bandwidth with the decreased latency for the complex IoT architecture. Ericsson Swedish telecom company (capital USD25 billion), Nokia Finnish telecom and data networking company (capital of USD18 billion) and Qualcomm American company (USD81 billion) are the major companies that positioned themself in the 4G and 5G development.

4G (Long Term Evolution – LTE) a previous technology of 5G is the challenging technology that is a reason for the rising number of smart devices connectivity. 4G uses the orthogonal multiple access that makes it difficult to support for the future IoT application. 5G has born to carry on this legacy that provide the combined framework needed for the latest IoT applications.

These wireless communication technologies bring the meaning to IoT because of the key advantage of global reach, scalability, diversity, low device cost, low deployment cost and long battery life.

WirelessHART:

It is a wireless technology that connects the field sensors and devices that manages a real-time data transmission. It finds application in the physical layer where a network mesh for a sensors and IoT devices in centralised management architecture. This standard is deployed in monitoring and control process that requires the real-time data communication between the sensors.

Sigfox:

Sigfox is one of the Low-Power Wide Area Network (LPWAN) technology used to build a wireless network of connected devices. It finds application in projects such as limited power sources (in the order of mA or tens of mA per transmission) and long-range mode (tens of km) of data transmission using IoT network. It works in the frequency range of 868 to 869 MHz in the EU region and 902 to 928 MHz in US region. Sigfox is a well suited technology for the IoT based water infrastructure management because it shows elevated performance in the high-density sensor networks, than other communication protocols which gets disturbed with collision.

Edge Computing:

The edge computing processes the data gathered from the field sensor or devices partially/completely enabling effective and responsive services. Edge computing is a recent paradigm that significantly reduces service latency and improves the quality of services (QoS) in data transmission. It handles the data processing tasks at the top of different edge devices (IoT gateways). It enables the utilization of both the hardware and network bandwidth by limiting cloud communication. This highly reduces the number and size of data transmission over the cellular network providing a better quality of service and quality of experience.

The data from the field is pre-processed at the edge before it reaches the application running on the cloud platform. These data about the consumption, detected event, leakages, and so on are made available to the end-users of the monitoring system via a web-based platform.

Conclusion:

The commercial mechanical water meter was found in the 1850s, the water-metering technology has seen a significant improvement in precision, accuracy, and reliability. With the breakthrough in the IT sector has made the AMI in water management a cost-effective way to collect data generated from the sensors.

With the invention of AMIs, the communication between the customer and service provider has become better. The market for such technologies is expanding, and the sensing and network communications technologies are improving. The municipal and agricultural sector is the main area where water resource management is a preliminary case. With the improved infrastructure design, and more efficient system operation those sectors get premium quality of service. For an advanced and autonomous water metering system data plays a crucial role. With the efficient water metering system, there is a possibility to improve energy efficiency. There is a huge need for gathering of data to realize the energy benefits, analyze the performance requirements to meet the specific installation needs, etc.

This digital solution here is able to tackle and moderate the protocols and standards in a competitive market. The flexible design allows this application to be easily adapted for the smart metering of other commodities.

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