MSIT Theses and Dissertations (2017)

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Browsing MSIT Theses and Dissertations (2017) by Subject "Automatic Meter Reading"

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    Automatic power meter reading based on Arduino micro-controller unit: case of the Kenya power and Lighting Company
    (Strathmore University, 2017) Keere, Samuel Ondieki
    Automatic Meter Reading (AMR), is the technology of automatically collecting data from metering devices (electric, water, gas) and transferring that data to a central database for billing and/or further analysis. Power utility firms have an obligation to bill their customers based on actual meter readings taken. However, provision of these services have had challenges. This leads to the issue of estimated readings and an inconvenient billing method that is based on incorrect readings. This is normally evident during the power meter-reading period when some power consumers influence clerks to evade paying their power bills. A common phenomenon in some cases is either where the same field clerks take wrong readings or end up over/underestimating the customer’s consumption. This ends up inconveniencing customers budgeting. In a bid to address this issue, Kenya Power Company has resorted to retrofitting the existing conventional post-paid meters with prepaid meters. This is however expensive and would take a long time to implement. This study proposes a solution for automatic meter reading by use of an ATmega328P MCU. This will entail an ACS712 current sensor that will be connected onto a power meter coupled to a LoRa gateway through a LPWAN for transmission of data to a cloud server for subsequent upload and analysis. Agile software methodology was used which allowed faster iteration and more frequent release with subsequent user feedback. This solution would not require replacement of the existing meters, making it cost effective and fast to implement. This study provides a solution that can enable the users have information on their readings, rate of billing and be able to report on any power issues affecting them. This will also help the power providers have their customers’ advice, which would aid in decision-making processes.