A Smart Voltage and Current Monitoring System for Three Phase Inverters Using an AndroidSmartphone Application – Flood solutions for East & Horn of Africa.

Because of the increasing advances in technology, smart systems are increasingly being used. These systems allow technicians, administrators, and managers to monitor and control the performance of devices from a safe distance. A monitoring system is very important when working in the field of three phase systems Moreso in this rainy season and the need to know what is happening around your power source is seminal. These programs can be installed on the user’s smartphone or company computers to allow employers to make decisions if there is an error.

The main objective of my paper this rainy month of April is to create a smart monitoring system based on an intelligent control system. My proposed system is called a smart voltage and current monitoring system or SVCMS. The SVCMS is designed to monitor the performance of a three-phase grid by measuring voltage and current. The SVCMS design consists of two parts; the first is the control system. This system has been designed using the Arduino Nano V3.0 as a microcontroller to read and calculate the RMS voltage and current from sensor units. The Arduino Nano V3.0 is an open-source platform that is very cheap, flexible, and has special-purpose data processing capabilities. Walk in at Nerokas, Thika and you will be sorted. Got mine at 4500/= only. The last part in the control system is the Bluetooth HC-05.  This  Bluetooth  HC-05,  is  one  of  several  types  of  wireless communication [20] (ZigBee, Wi-Fi, etc.) unit placed between the control system and the end user (monitoring system).

The aim of this work was to design and implement a low cost and safe three phase measuring system and to design a smartphone application to monitor the data received from the three phase measuring system during these flooding season. My SVCMS has been designed to measure three phase voltages and currents for all three phase systems that have a line to ground voltage of less than 250 VAC with a current value of less than 30 A.

There are more methods for controlling and monitoring a three phase circuit depending on the controller or the type of display for the results of the voltage and current. In my paper, a new method for monitoring and displaying the three phase system is given; this method is called the smart voltage and current monitoring system, or SVCMS, where a smartphone is used instead of traditional methods like an LCD display or an analog  method  for monitoring and displaying the results.  It consists of two major parts which are the control and monitoring parts.  The control part has four branches which are: a voltage sensor unit, a current sensor unit, the Arduino Nano V3.0 unit, and wireless communication unit (Bluetooth device), while the second part contains the monitoring part that monitors the voltage and current for three phases using the Android smartphone application which is written using the  JKUAT  App  Inventor  2, an open  source software  platform available  from Google for Android project applications.

Now,  the  control  part  I will break it down for the reader(s).  It mainly consists of two  sensors  for  measuring  the voltage  and  current.  The  voltage  sensor  contains  the  transformer  and  two  op-amps  (LM358). and the voltage sensor circuit in the pic below, the Matlab Simulink simulation of the three phase voltage system is shown below as well. The input voltage sine wave is offset equal to zero and upper with lower voltage of 230 V. The output voltage should range between 0 and 5 V for the microcontroller which is offset around 2.5 V. This circuit is used to reduce the voltage in order to deal with the high voltage.

Matlab/Simulink of a three phase voltage system

Simulation result (both input and output voltages)

My smart voltage and current monitoring system (SVCMS), is designed and implemented to measure and monitor three phase voltages and currents. The SVCMS model is more cost effective than similar models that use heavy current transformers (CTs). It is also safer than having to measure the mains voltages very often. It is a low cost and easily applicable model for measuring and monitoring three phase system performance as compared with other models. Any technician can also work with the domain like virtual reality. The monitoring system uses a new Android smartphone application designed by MIT App Inventor 2. This application receives the three phase RMS voltage and current data from the Bluetooth device (HC-05). The SVCMS has been tested successfully internally at our trial R&D labs in KE, SML, MZQ and US.

The future of smart monitoring system model and applications is to replace the Bluetooth wireless communication system by Internet of Things (IOT) technology. This technology will be used to connect the sensors and devices over the internet by allowing them to talk to us, work in applications, and interact with each other. I hope KPLC & SOMPOWER, team members are taking notes of this nifty idea(which I haven’t patent) as is work meant to improve the lives of every citizen in East and Horn of Africa.

Compiled by : Samwel Kariuki

Date: 30th April 2024

Artificial Intelligence in Construction Projects within East and Horn of Africa:

INTRODUCTION

Al intelligence (AI) is a fast-growing innovative technology that will have a huge impact on projects and project management practices in the forthcoming years. The purpose of this paper is to contribute to project management theory and practice in the construction industry by analyzing the expectations of project professionals. A mixed method based on an international survey and semi-structured interviews was applied. The results show that construction project practitioners are looking for AI solutions to support the quantitative processes mainly related to scope, schedule, cost, quality, and risk management. However, the human-related processes, such as communication and stakeholder management, are not expected to be directly enhanced by AI, although might benefit from it indirectly. The findings also demonstrate a difference between amplifying and accelerating countries, where somewhat surprisingly the latter are more ready to adopt AI in their projects.  

The continuously rapid advancement in technology Moreso in East and Horn of Africa is changing almost every aspect of organizational and managerial activities. The fast-growing discipline of Artificial Intelligence (AI) gets more and more attention from practitioners and academics in different fields of management, and is expected to disrupt the field of project management (PM).

Projects in the construction industry had taken a predominant role from the inception of the PM field. Even though new sectors and non-traditional industries also apply PM practices, the construction industry in East and Horn of Africa still constitutes a major part of the evolving PM body of knowledge. As a well-established domain of professional PM, the construction industry can, therefore, be an interesting case to investigate how new technologies, such as AI, have the potential to improve and reshape the profession.

AI was initially introduced in the 1950’s aiming to replicate human intelligence using computer programs. Although throughout the years the field of AI experienced major fluctuations, mainly due to a mismatch between the level of expectations and the level of available applications, it seems that current AI technologies are mature enough to provide substantial improvements in different   aspects   in   the   workplace, including   project operational and managerial processes.

     The aim of this paper is to analyze construction project practitioners’ expectations with regard to AI being applied to PM processes and practices. The paper starts with an introduction to AI. The next section reviews AI applications in the context of construction PM, by knowledge areas. Then, the research question and methodology are described, followed by reporting the research findings. The paper is finalized with a discussion of the main insights and concluding remarks on the limitations of the current study and directions for further research.

The current paper adopts the recent approaches, therefore suggesting that AI is based on the increasing capabilities of technology to analyze data, learn, perform tasks that are currently performed by humans, and adaptively interpret external conditions. In the context of project management, it means that AI technologies can be used to autonomously perform routine tasks and to support the project manager’s work by recommending preferred decisions and actions based on the machine’s competence to be adaptive to different environments and situations.

AI   technologies   are   classified   based   on   levels   of specialization and intelligence. Narrow AI (NAI) refers to applications that are focused on a single subset of cognitive abilities to learn and do well only what they were designed for, within a specific spectrum, therefore usually used to automate specific tasks and improve efficiency. Examples in the context of project management might include optimal resource allocation, optimal project schedule, or optimal contract prices for the procurement of goods. General AI (GAI) includes intelligent applications that can autonomously learn and perform as, or even better than, humans on a wide range of tasks. GAI for project management might be in the form of project portfolio selection, analyzing customer requirements, or optimizing operation and site safety. The highest level of AI, named Super AI or superintelligence, refers to systems that exceed human intelligence and abilities, defined by Boström as “intellects that greatly outperform the best current human minds across many very general cognitive domains”. However, there is no consensus on if and when it will be possible to develop superintelligence systems, and there is a wide agreement that the current state of the art in AI cannot support superintelligence.

Compiled by : Samwel Kariuki

Date: 12th April 2024