Today, government or private organizations need to personally visit the industries for checking the energy ratings. This is quite difficult to visit and audit the energy ratings. As day-by-day industries are growing, it would be more difficult to audit personally. There may be case of corruption in the audit of energy measurement. To cure these problems wireless energy meter can be installed to accurate and time to time measurement.
Our project is a blend of IoT, AI, and web development. So we divided our team into three section, one section would focus on hardware integration and optimization, another one on prediction models and the last one would focus on web application and Android application development. First, we create and test all the separate entities and then integrate it to create the final product. In this way all the entities can be tested rigorously as well as work can be completed parallelly. This approach would significantly reduce the time and assure well tested and optimized entities.
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The novel solution which we propose here is designed so as to tackle the following issues :
• Wastage of electrical energy. This is taken care of as this invention provides the correct data of the requirement of electricity to the power station, so that the power station knows how much amount of electricity is needed to be produced for the next session.
• The traditional electricity meter measures the total and cumulative energy consumed by the electrical appliances at the property and required the meter to be read manually either by customer or by meter reading personnel on behalf of the energy provider. Manually reading the meter in this way means gaining the physical access to the property where the meter was installed, and where there was a lack of access which affects the result in estimation of power consumed.
• Also when suppliers want to cut the electricity connection of the particular property the only way to do this is in manual way for which they need to appoint the personnel it means electricity company needs to lose money and time both at a time.
• Also, the customers who consume electricity do not have any idea about their use of electricity and also they do not have idea about their consumption of electricity and how much bill they would going to pay after a month.
Smart meter measures the energy being used at a much greater resolution, which provide an improved understanding of the electricity consumption it means bill can be generated accurately based on up-to-date energy consumption. Also, the electricity supplier company has the access to each and every electricity meter unit of the city so that the supplier company can cut off the electricity connection of any smart meter unit if their is delay by the customer corresponding to the smart meter unit in paying the electricity bill, so after installing this machine there is no need of appointing the personnel for collecting the electricity reading and cutting off the electricity connection manually the smart meter will make this complex system easy and wireless which is more convenient than the previous one.
In this era where computer-based technologies dominate every section of our society, we are still largely dependent on exponentially declining organic fuels for electricity. In such a scenario, any kind of electricity wastage must be optimized. About 22.5 % of the total electricity, dissipation directly depends on the trans- portation network characteristics and the mode of operation.Powerhouses are unable to predict efficiently the total consumption of electricity demanded by a city which leads to enormous “load factor effect“ losses. But with the emergence of IoT and AI, we can now estimate the total amount of energy required by every block in a day efficiently. This estimation will help powerhouses to determine their electricity supply and counter their losses dramatically. The data received from the smart meter unit which installed in each property of the city would be stored in the database software of the server which is at the electricity supplier company, now this received data from the smart meter is using to train the (ML) machine learning algorithm then after the certain time the whole system will be able to predict the amount of electricity required to the city for the upcoming session even before the session has been started. The smart electricity meter unit is also trained with (ML) an algorithm which provides data of usage of electricity to each consumer also the smart meter will send the message to the user about his expected bill for the next month so now after installing the smart meter unit in his property he knows how much money he would have to pay, even before the starting of the month.
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Remote meter reading - It saves the cost of a human meter reader and the resulting mistakes and it also allows more measurements, and remote provisioning.
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Provide remote access for switching off or on the power supply of its users. Thereby, providing a better mechanism to check for bill-defaulting users.
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Identify anomalies and thefts of electricity by analyzing the consumption data of its users.
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Providing real-time data useful for balancing electric loads and reducing power outages (black- outs). Thereby, also saving electricity wastage by surplus production.
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Enabling dynamic pricing or Time-of-use Tariffs (raising or lowering the cost of electricity based on demand).
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Consumers can be informed remotely (historical data) or locally (real-time data) on energy costs. Also, they can reduce costs by increasing energy consumption during off-peak cheaper tariff periods.
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Notifications can be sent to users on this application whenever the admin(s) find the possibilitie of anomalies or thefts by analyzing the power consumption.
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Machine learning algorithms (For example : ARIMA) can be leveraged to estimate the power consumption of users on a monthly/yearly basis.
Harshendra Shah : Android and Web Application
Heet sankesara : Django Server, REST API and Interfacing
Khilan Ravani : Arima Implementation and Documentaion
Kshitij Palghane : Hardware Architecture Design, Implementation and Testing
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