What is IDO IoT Resource Meter?

IDO IoT Resource Meter is a solution that meets many needs at the same time:

• it allows for multi-level control of resource consumption, both by the administrator and resource users;
• facilitates the administration of buildings, minimizes the number of on-site visits;
• helps to detect failures and threats early;
• reduces waste and protects the environment.

Due to its design, the system can be installed in new buildings but it’s also enough to carry out a simple modernization of existing systems to make it work, even in very old houses. This makes our solution perfect for locations such as:

• housing communities and cooperatives;
• premises managed by real estate agencies;
• short-term rental premises;
• offices and service premises.

How does work?

Before the first data is sent to the system, the infrastructure individual for the network in question should be prepared. It will be different for individual premises in distributed locations (e.g. buildings maintained by agencies) and located in the same building (e.g. offices), but the basic building blocks remain the same.

1. Infrastructure preparation

Before the first data is sent to the system, the infrastructure individual for the network in question should be prepared. It will be different for individual premises in distributed locations (e.g. buildings maintained by agencies) and located in the same building (e.g. offices), but the basic building blocks remain the same. The necessary elements include:

• resource (power & water) meters operating in the unlicensed (with no additional charges) band 868 MHz. For that purpose we used:
  1. LoRa – useful especially where safety is particularly important or access to devices is difficult, so a long working time (up to several years) on standard batteries is of utmost importance, is characterized by extremely low energy consumption (up to 20 years on standard batteries) and a long-range (up to 5 km in the city).
• IoT gateway. Usually, one gateway per building is enough, but due to the low bandwidth associated with the standards used (e.g. LoRa – 20b/s-41 Kb/s), it is enough to add more gates where the transfer would be limited given the size of the packets (e.g. in multi-family blocks).

2. Cloud computing

The data stream flowing from the gates is then stored in database clusters on the AWS cloud. The events generated by the gates are registered in the event bus and from there sent to the invoicing and analytical system (see below). The system analyzes the information and returns it to the bus, from where it can be downloaded by the user, e.g. in the form of a resource consumption graph.

This approach has many advantages:

• It allows the autonomy of services to be maintained.
• It gives great opportunities to scale and optimize the costs of the solution.  Moving to a Software as Service architecture allows billing only while resources are in use. This reduces the costs of the entire project and optimizes the operation of the system in the event of a cyclical load of resources.
• Provides ease of invoicing for the customer –  the customer receives an invoice for processing a certain amount of data. It is also possible to invoice e.g. by the number of active gates.

3. Data processing and analysis

The data obtained are transferred to the invoice and analytical system IDO IoT Resource Meter. This tool has a dual function:

1. It monitors the consumption of utilities, and cyclically generates and sends invoices for the users. Thanks to the automation of the process, errors resulting from oversights, e.g. omission of an invoice, errors in addressing, etc. are eliminated.
2. A neural network analyzes data and predicts consumption and trends based on historical data from the server. If the forecast exceeds the expected values, the system will send a direct notification to the user (via e-mail, SMS, or in the app). In this way, possible failures resulting in wasting resources can be detected faster and precisely located.For example:
   1. Water consumption in the entire building has slightly increased, and the individual indicator on the single premise records greater consumption. A leaking seal in the faucet is causing the problem. The locator of the premise will receive a notification of the defect.
   2. Water consumption for the entire building has risen sharply, but individual meters have not registered greater consumption. Probably the problem is a leaking pipe carrying water to the entire building. The owner of the building will receive a notification of the defect.
3. Sending invoices and preparing a utility consumption forecast completes the IDO IoT Resource Meter operation process.

The system uses the TensorFlow library, thanks to which we achieved several benefits:

1. The TF library is open-source, which means that using it in the IDO IoT Resource Meter project does not increase the costs associated with software licensing. In addition, a committed, large community around the project guarantees security, quick debugging, and access to ready-made elements that facilitate the expansion of the program with new functions.
2. Built-in neural network (AI) functions that recognize data ensure proper administration and dispatch of invoices.
3. The elements responsible for machine learning (ML) draw regularities from systematized data and allow forecasting future consumption, as well as informing about deviations from the rule.

The IDO IoT Resource Meter project focuses on implementing intelligent resource management systems in modern buildings. This initiative leverages IoT technology to provide precise usage monitoring, aiming to enhance resource management efficiency. By integrating smart meters and real-time data analytics, the system helps in detecting leaks, preventing water wastage, and ultimately promoting sustainable water consumption. This innovative solution is designed to support both residential and commercial buildings in their efforts to achieve more effective and eco-friendly resource management.