1. Introduction

Renewable energies (REs) are a set of means of generating energy from unlimited (on a human scale) sources or resources, available without time limits or recoverable more quickly than they are consumed. Renewable energies are often spoken of as opposed to fossil fuel energies, whose stocks are non-renewable and limited: coal, oil, natural gas. The renewable energies are unlimited which produced from many sources such as the wind and the ray of sun [1].

REs are often referred to as “clean energies” or “green energies”. The environmental effect of their operations is very low which makes them a major element in companies’ Corporate Social Responsibility (CSR) strategies in terms of sustainable development. The exploitation of renewable energies theoretically generates few pollutants: in particular, electricity of renewable origin emits very little CO2 especially when compared to fossil fuels such as coal. For this reason, renewable energies are a particular vector of the fight against global warming. They are also considered as a factor of resilience because they allow decarbonized and decentralized productions.

There are different energy sources that produce several types of renewable energy. Maybe the most known is still the solar energy. This type of energy comes directly from the capture of radiation coming from the sun. Specific sensors are used to absorb the energy of the solar radiation and rebroadcast it according to two main modes of operation:

• Solar photovoltaic (solar photovoltaic panels): solar energy is captured for the production of electricity.
• Thermal solar (solar water heater, heating, solar thermal panels): solar heat is captured and is redistributed, and more rarely used to produce electricity.

The global market stagnated last year, with around 98 GW deployed. For 2019, the experts expect stronger solar growth, PV Market Alliance warned its forecast for 2019 that global solar installations would grow by about 20% to as much as 120 GW, and volume of 180-200 GW by 2022 [1].

In the recen years, Morocco has encaged in a startegy of alternatives energies, all determneted to move from a country importing all its oil and gas needs to major producer renewable  energy (figure2), whereas it  depended totally, and until a near past, of the outside for the energies needs.

Through its renewable energy development strategy, Morocco aims to ensure its relativity energy independence, contribute to reducing emissions and produce renewable energy that will shape the future of human consumption.

Figure 1: The global solar PV market will grow stronger than expected according to IHS Markit.

The kingdom has made tremendous progress in the fieled of green enrgy since 2009 and has set ambitious goals in the field of clean energy. The Moroccan strategy aims to increase the share of renewable energies to 42% by 2020 and 52% by 2030. In addition to the gaol of reducing energy consumption  to 12% by 2020 and 15% thanks to energy efficiency[2,3].

For this reason, the average power in next-generation installations is increasing day by day, with the need for systems capable of supervising and monitoring installations in a permanent form and interacting with all elements, thus ensuring a high level of optimal efficiency, from a technical as well as an economical point of view. At this point, it is essential to develop new infrastructures and technologies, to install remote monitoring system that allows a significant reduction in time response and keeps track on the PV energy production from a given PV plant[4].

The supervision, or monitoring, of isolated PV plants makes it possible to evaluate the quality of operation of the system and, conversely, to detect possible anomalies. It is generally composed of a data acquisition and storage system, a signal processing or analysis software, and a display. In some cases, the system is coupled with sunshine and temperature probes. Many PV inverter manufacturers offer their own monitoring connected to their inverter. Most often the data acquisition system is integrated into the inverter and its consultation is done by dedicated software. Sometimes, the supervision is composed of a datalogger which makes it possible to centralize the data of several inverters and possibly to make them accessible remotely via internet.

Figure 2: Photovoltaic energy development in Morocco.

Our objective in this article is to present the developed wireless monitoring system. The process is divided into two parts; the first part is the description of the used hardware mainly built around the Raspberry Pi3, the second part is the software development including the installation and the configuration of open source applications to settle the incompatibilities problem with open source systems. The proposed monitoring system will communicate with the inverter to retrieve, transfer and process data using a new open-source application in a completely remote and wireless way.

The paper is divided into three sections. We will start with a discussion on the encountered problematic and propose an adequate solution. The second section describes the choice of equipment for the designed system to meet the desired requirements. Finally, the last section presents our proposed wireless system for monitoring photovoltaic plants. The system is divided into three main parts: The data acquisition from the inverters via Bluetooth, the data processing in Raspberry Pi3[5] and the data transfer via Wi-Fi.

2. Problematic

There are different solutions to monitor the production and operation of an inverters or photovoltaic panels. The main selection criteria and questions to ask are:

• What information and settings will be saved and viewed?
• How will this information be saved and how will it be consulted?
• What will be the sources of the information: electricity meters, inverters, datalogger?
• What is the cost of the production tracking and monitoring system?

Nevertheless, the existing PV monitoring applications in the market are limited and incompatible with most of the operating systems. Moreover, the manufacturers of power plants tend to design systems that do not meet the desired constraints and contain some drawbacks [6].

2.1. The encountered situation

The situation we have is a PV installation composed of SMA electrical inverters [7] connected to six photovoltaic panels. The inverters allow the transformation of the generated direct current into an alternative current. In our photovoltaic system, these inverters are provided with a measurement and processing system, allowing the storage in real-time of data related to electricity generation.

Figure 3: The need of the operator presence in the field to retrieve data

The recovery of stored data can be provided in two ways; either via wireless Bluetooth or wired Ethernet. Practically, this monitoring system has a major issue: regardless of the used recovery method, there is always a need for an operator to be in close contact with the installation (figure 3). While the Bluetooth offers a wireless connection to the inverters, it does not allow real-time data recovery from distant locations.

2.2. Objectives

The main objective of this work is the development of a PV monitoring system to transfer data in real-time to a remote operator. To implement such a system, we should be ensuring the following points:

• A communication with the inverters via Bluetooth protocol.
• The data recovery in Bluetooth mode.
• The pre-treatment of data with SBF application.
• The wireless transfer of data to the server via WiFi.
• The data visualization by the operator in real-time via the Internet.
• The creation of a web interface for the storage and processing of retrieved data on the supervision machine.

The proposed system will provide us with a wireless communication to the inverters via the Bluetooth protocol. Once received, the data will be pretreated then transferred to the remote control machine trough the network via Wi-Fi or directly stored in an online database (figure 4).

3. Equipment

3.1. Comparative study

The choice of equipment was constrained by some specifications.

The recommended equipment should:

• Have a reasonable price;
• Support the Bluetooth and the WiFi protocols;
• Have at least a 1 GHz CPU and a 1 Gb RAM;
• Card compatible with the most popular operating systems;
• Have a rich library and documentation.

There are multiple variants of nano-computer on the market that, relatively, encounter those conditions such as Orange PI, Odroid, Banana Pi M3 , Raspberry PI3 and Arduino. We chose the Raspberry Pi3 card after a comparative study, because it is the most appropriate among all the other cards[7].

Indeed, the Raspberry Pi is the undisputed heavyweight champion of the world. Beside it is most powerful, the most compact, and the cheapest; its devotees are legion, several developers use it in several projects, which means that its use is more convenient than others are.

3.2. Raspberry Pi

The main component on which our system is built is the Raspberry card.

The Raspberry Pi3 is a small integred computer in the size of the hand, with a price not exceeding 40 $  and most-lowest power consumption, less than 5 Watt. Designed at the University of Cambridge to help to teach programing, electronics and intelligent control systems at the same time. Its performance making this nano-computer  astonishing success in both the educational and applied fields [5].

 It works not only with numerous variants of Linux operating system but also with Microsoft Windows OS such as Windows 10 and phone operating systems.

Numerous versions of Raspberry Pi3 have been made from the time when the original Model B was created, each bringing either upgraded specifications or features specific to a particular use-case. All models feature a Broadcom on Chip (SoC) system and are compatible with a 700 MHz to 1.4 GHz compatible CPU and an integrated memory ranging from 256 MB to 4 Gb.

For our choice of equipment,  our electronic and computer system is based on Raspberry PI3 (figure 5), its performances are:

• 4 GHz processing CPU
• 1Gb RAM
• Wi-Fi 802.11n (150 Mbit/s) and Bluetooth 4.1 (24 Mbit/s)

3.3. Operating System

Like any computer system, the  Raspberry Pi requires an operating system OS to work. Choosing an operating system is difficult task. The choice is based on the needs of the user but also on his tastes and preferences.it is thus difficult to say that such a system is the best. but for our case the adequate OS is Raspbian.

Rasbian is the reference OS for Raspberry Pi. It is based on Linux Debian and is updated very regularly. Optimized specifically for Raspberry PI, it is a versatile distribution.

The greatest strength of Raspbian it not even the OS itself but its community and its reputation well-known by developers around the world [7].

Figure 4:  Raspberry Pi3

4. Overview of the proposed PV wireless monitoring system

Our proposed electronic and computer system (software and hardware) is constructed around six photovoltaic panels and their inventers. Each inverter is equipped with a Bluetooth module that will communicate with the Raspberry Pi3. This latter pays the main role of putting the link between the inverters and the servers in order to retrieve the data and store it directly in on line database (figure 6).

The installed wireless monitoring, give us the measurement of several quantities parameters by which we can qualify our panels performances. The quantities measured are Current, Voltage, and Energy as electrical parameters. Illumination and Temperature as metrological parameters.

Three parts are included in our proposed wireless monitoring system, which are:

• The data acquisition.
• The data processing.
• The data storage and transfer.

Figure 6: Prototype of our wireless PV monitoring system

4.1. Data acquisition

As stated in the second section, the inverters are associated to a system of storage of several parameters in real time. Our system will retrieve it remotely via Bluetooth Protocol.

Bluetooth is a radio communication; this type of technology does not require a large amount of energy. Bleutooth technology starts by generating radio waves. The value of frequency, when generated, is 2.45 GHz, a universally recognized value for industrial, scientific and medical devices. It is possible to establish several connections using Bluetooth in the same area; this will not affect them because there are different frequencies for each device at different times, called scattered frequency hopping. This technology allows the use of more than 79 frequencies randomly in a certain area. Note that the value of the frequency changes constantly, which means that the value of the frequency will be submitted 1600 times per second by a Bluetooth device, as result the radio spectrum will benefit a group of peripherals.

The Bluetooth is a protocol with Master/Slave architecture. Master has to connect with up to seven slave simultaneously, which call piconet.  In the piconet there are up to 255 slaves in parcked mode. Thus, give us the chance to connect many inverters [8].

4.2. Data processing

 For the data processing step we use the either Windows Sunny Explorer or SBFSpot [9].

The installation of the Sunny Explorer application is now possible after the launch of the Windows 10 operating system on the ARM platform of Raspberry PI3, which resolves our old compatibility problem between Windows applications and the ARM architecture.

Figure 7: Organization of a Bluetooth network into scatternet and piconet

The proposed alternative is to use the SBFSpot application and the PVOutput [7] is an open source project to get actual and archive data out of the inverters over Bluetooth, it allows retrieving data from the inverters via Bluetooth, while the PVOutput stores the data and processing them into graphical figure. We also note that we developed our own interface application for the results visualization.

Finally, by those applications we are allowed to process the received data from our station (figure 8).

Figure 8: Different electrical parameters retrieved from the PV installation

4.3. Data transfer

The next phase is to transfer processed data to the control machine via Wi-Fi. We have two situations for control our power station. The control machine is either inside the institution or outside of it. For each situation, we used different secure method of transfer: SSH, secure and simple method of transfer. VNC virtual network computing, secure and complex graphical method.

Both methods require the installation of a server on the Raspberry PI3 card and a client on the control machine.

Data transfer via SSH

SSH [10], or Secure Socket Shell, is a network protocol that allows administrators to remotely access a computer in complete security. The Secure Shell protocol is a compensation of the previous protocol Telnet service where the transfer of information was open and vulnerable; allowing users of certain programs to spy on sensitive information such as username and password, while SSH is more powerful than its predecessor by encrypting the data transmitter between the user and server.

SSH is an open source application that allows you to open a terminal session on Raspberry PI3 from a command line on the host computer. By default, SSH is installed on the Raspberry PI3, but is disabled for security reasons. The first thing to do is to activate SSH on your Raspberry PI3. For that, you just have to connect the MicroSD card of Raspberry Pi on our computer, to go on the map, and to create a file named ssh in the boot partition, then install the SSH client on the control machine using the PuTTY emulator.

Data transfer via VNC

To control remotely in full desktop we use VNC [11].

VNC, or Virtual Network Computing, is a protocol that allows distant control of one computer by another. When using VNC, two different parts of the software are used.

The first part is the VNC server is installed on the Raspberry Pi3 side. The second part is the VNC client. It is installed on the control machine side, by which we will control and connect to the server to execute our requests remotely.

After installing and enabling VNC server by SSH command. Now we should simply put the address of our card in order to get remote graphic control of the raspberry desktop.

On the other hand, the choice of the machine address is related  to the previous situations, either outside the institution and inside of it. If the control machine is inside so we used the RealVNC with a private IP address, , while if the machine is outside, we will need to use RealVNC with a pair containing a public IP address and a specified port assigned to the private address of the Raspberry card. In the case of a dynamic public address, use the dynamic No-IP DNS service.

5. Conclusion

In this article, we proposed the design and tests of a wireless monitoring system from a remote location based on three layers: the acquisition, the processing, and the storage and web service layers. The proposed system comes as a more compatible, flexible, and powerful system by solving the faults in our old system.

The main advantage of this supervision system is that it is a low-cost and low-power system with highly scalable software. The system is built around a nano-computer (the Raspberry PI3 card), a wireless protocol (Wi-Fi and Bluetooth) and an open-source application. Thus, providing us with a connection to the inverters and process the received data remotely and finally present them directly on our processing machine.

After some modifications and improvements, the proposed remote system, and the implementation of the application. Our system of monitoring has been validated and successfully tested by field trials.

Conflict of Interest

The authors declare no conflict of interest.

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41. Mohammed Hadwan, Rehan Uallah Khan, Khalil Ibrahim Mohammad Abuzanouneh, "Towards a Smart Campus for Qassim University: An Investigation of Indoor Navigation System", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 831–837, 2020. doi: 10.25046/aj050699
42. Azani Cempaka Sari, Natashia Virnilia, Jasmine Tanti Susanto, Kent Anderson Phiedono, Thea Kevin Hartono, "Chatbot Developments in The Business World", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 627–635, 2020. doi: 10.25046/aj050676
43. Jojo Blanza, Lawrence Materum, "Interface for Visualization of Wireless Propagation Multipath Clustering Outcomes", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 544–549, 2020. doi: 10.25046/aj050665
44. Mokhlis Salah-eddine, Said Sadki, Bahloul Bensassi, "Microcontroller Based Data Acquisition and System Identification of a DC Servo Motor Using ARX, ARMAX, OE, and BJ Models", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 507–513, 2020. doi: 10.25046/aj050660
45. Kin Yun Lum, Yeh Huann Goh, Yi Bin Lee, "American Sign Language Recognition Based on MobileNetV2", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 481–488, 2020. doi: 10.25046/aj050657
46. Puttakul Sakul-Ung, Amornvit Vatcharaphrueksadee, Pitiporn Ruchanawet, Kanin Kearpimy, Hathairat Ketmaneechairat, Maleerat Maliyaem, "Overmind: A Collaborative Decentralized Machine Learning Framework", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 280–289, 2020. doi: 10.25046/aj050634
47. Khalid Ait Hadi, Rafik Lasri, Abdellatif El Abderrahmani, "Inferring Topics within Social Networking Big Data, Towards an Alternative for Socio-Political Measurement", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 155–159, 2020. doi: 10.25046/aj050618
48. Yanlin Pan, Jia Rui Thong, Pik Kee Tan, Siong Luong Ting, Chang Qing Chen, "Laser Deprocessing Technique and its Application to Physical Failure Analysis", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 1273–1281, 2020. doi: 10.25046/aj0505153
49. Paul Cabacungan, Carlos Oppus, Gregory Tangonan, Nerissa Cabacungan, John Paul Mamaradlo, Neil Angelo Mercado, "Design and Development of Electronic Sensor and Monitoring System of Smart Low-cost Phototherapy Light System for Non-Invasive Monitoring and Treatment of Neonatal Jaundice", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 1233–1246, 2020. doi: 10.25046/aj0505149
50. Sherif H. ElGohary, Aya Lithy, Shefaa Khamis, Aya Ali, Aya Alaa el-din, Hager Abd El-Azim, "Interactive Virtual Rehabilitation for Aphasic Arabic-Speaking Patients", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 1225–1232, 2020. doi: 10.25046/aj0505148
51. Mounir Amraoui, Rachid Latif, Abdelhafid El Ouardi, Abdelouahed Tajer, "Feature Extractors Evaluation Based V-SLAM for Autonomous Vehicles", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 1137–1146, 2020. doi: 10.25046/aj0505138
52. Adrian Florea, Valentin Fleaca, Simona Daniela Marcu, "Innovative Solution for Parking-Sharing of Private Institutions Using Various Occupancy Tracking Methods", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 808–819, 2020. doi: 10.25046/aj050598
53. Tri Nhut Do, Quang Minh Pham, Hoa Binh Le-Nguyen, Cao Tri Nguyen, Hai Minh Nguyen-Tran, "Development of a Wireless Displacement Estimation System Using IMU-based Device", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 781–788, 2020. doi: 10.25046/aj050595
54. Khaldoon Fadhel Brethee, Ghalib Rzayyig Ibrahim, Rashaq Abdullah Mohammed, "Using Envelope Analysis and Compressive Sensing Method for Intelligent Fault Diagnosis of Ball Bearing", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 370–375, 2020. doi: 10.25046/aj050546
55. Ladislav Burita, Ales Novak, "ISR Data Processing in Military Operations", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 314–331, 2020. doi: 10.25046/aj050540
56. Oleksandra Mrykhina, Lidiya Lisovska, Ihor Novakivskyj, Terebukh, Valentyna Zhukovska, "Method of Modelling Prices for R&D Products in the Case of their Transfer from Engineering Universities to the Business", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 80–93, 2020. doi: 10.25046/aj050512
57. Nghia Duong-Trung, Luyl-Da Quach, Chi-Ngon Nguyen, "Towards Classification of Shrimp Diseases Using Transferred Convolutional Neural Networks", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 724–732, 2020. doi: 10.25046/aj050486
58. Natalya Chernova, Victor Chernov, Margarita Emelianova, Raisa Akhunzianova, Danil Sukhopluev, "Social-Interactive Learning Concept Used for Electronic Educational Resource “Post-Graduate Foreign Language” and the Obtained Learning Curve", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 655–659, 2020. doi: 10.25046/aj050478
59. Mohammed Qbadou, Intissar Salhi, Hanaâ El fazazi, Khalifa Mansouri, Michail Manios, Vassilis Kaburlasos, "Human-Robot Multilingual Verbal Communication – The Ontological knowledge and Learning-based Models", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 540–547, 2020. doi: 10.25046/aj050464
60. Roberta Avanzato, Francesco Beritelli, "A CNN-based Differential Image Processing Approach for Rainfall Classification", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 438–444, 2020. doi: 10.25046/aj050452
61. Hana Yousuf, Said Salloum, "Survey Analysis: Enhancing the Security of Vectorization by Using word2vec and CryptDB", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 374–380, 2020. doi: 10.25046/aj050443
62. Shahab Pasha, Jan Lundgren, Christian Ritz, Yuexian Zou, "Distributed Microphone Arrays, Emerging Speech and Audio Signal Processing Platforms: A Review", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 331–343, 2020. doi: 10.25046/aj050439
63. Kanishk Rai, Keshav Kumar Thakur, Preethi K Mane, Narayan Panigrahi, "Design of an EEG Acquisition System for Embedded Edge Computing", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 119–129, 2020. doi: 10.25046/aj050416
64. Ivan Boban, Alen Doko, Sven Gotovac, "Sentence Retrieval using Stemming and Lemmatization with Different Length of the Queries", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 349–354, 2020. doi: 10.25046/aj050345
65. Dennis Luqman, Sani Muhamad Isa, "Machine Learning Model to Identify the Optimum Database Query Execution Platform on GPU Assisted Database", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 214–225, 2020. doi: 10.25046/aj050328
66. Sally Almanasra, Ali Alshahrani, "Alternative Real-time Image-Based Smoke Detection Algorithm", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 123–128, 2020. doi: 10.25046/aj050316
67. Aditi Haresh Vyas, Mayuri A. Mehta, "A Comprehensive Survey on Image Modality Based Computerized Dry Eye Disease Detection Techniques", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 748–756, 2020. doi: 10.25046/aj050293
68. ?ahin Aydin, Mehmet Nafiz Aydin, "A Sustainable Multi-layered Open Data Processing Model for Agriculture: IoT Based Case Study Using Semantic Web for Hazelnut Fields", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 309–319, 2020. doi: 10.25046/aj050241
69. Hind El Hassani, Nour- Eddine Boutammachte, Sanae El Hassani, "Optimization of Low Temperature Differential Stirling Engine Regenerator Design", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 272–279, 2020. doi: 10.25046/aj050235
70. Lenin G. Falconi, Maria Perez, Wilbert G. Aguilar, Aura Conci, "Transfer Learning and Fine Tuning in Breast Mammogram Abnormalities Classification on CBIS-DDSM Database", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 154–165, 2020. doi: 10.25046/aj050220
71. Jorge Castro Bedriñana, Doris Chirinos Peinado, Richard Peñaloza-Fernández, "Lead Bioaccumulation in Root and Aerial Part of Natural and Cultivated Pastures in Highly Contaminated Soils in Central Andes of Peru", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 126–132, 2020. doi: 10.25046/aj050216
72. Mimouna Alkhonaini, Hoda El-Sayed, "Performance Evaluation and Examination of Data Transfer: A Review of Parallel Migration in Cloud Storage", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 57–63, 2020. doi: 10.25046/aj050207
73. Johannes Linden, Xutao Wang, Stefan Forsstrom, Tingting Zhang, "Productify News Article Classification Model with Sagemaker", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 13–18, 2020. doi: 10.25046/aj050202
74. Ehab Mohamed Zakaria, Shawky Hamed Arafa, Maged Naguib Fahmy Nashed, Salah Ghazi Ramadan, "Fuzzy Logic Control Management with Stand Alone Photovoltaic – Fuel Cell System", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 1, pp. 424–430, 2020. doi: 10.25046/aj050154
75. Brian Meneses-Claudio, Witman Alvarado-Diaz, Avid Roman-Gonzalez, "Classification System for the Interpretation of the Braille Alphabet through Image Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 1, pp. 403–407, 2020. doi: 10.25046/aj050151
76. Guillermo Kemper, David Atencia, Ivan Ortega, Roberto Kemper, Alejandro Yabar, "An Algorithm for Automatic Measurement of KI-67 Proliferation Index in Digital Images of Breast Tissue", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 1, pp. 201–211, 2020. doi: 10.25046/aj050126
77. Mohamed Bakry El_Mashade, Haitham Akah, Shimaa Abd El-Monem, "Windowing Accuracy Evaluation for PSLR Enhancement of SAR Image Recovery", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 1, pp. 48–57, 2020. doi: 10.25046/aj050107
78. Temitayo Olayemi Olowu, Mohamadsaleh Jafari, Arif Sarwat, "A Multi-Objective Voltage Optimization Technique in Distribution Feeders with High Photovoltaic Penetration", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 6, pp. 377–385, 2019. doi: 10.25046/aj040648
79. Sushri Mukherjee, Sumana Chattaraj, Md. Irfan Khan, Dharmbir Prasad, Pradip Barua, Harish Agarwal, "Transmission Line Restoration Using ERS Structure", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 5, pp. 394–400, 2019. doi: 10.25046/aj040551
80. Manel Jomaa UR-LAPER, Mohamed Yassine Allani UR-LAPER, Abdelkader Mami UR-LAPER, "Modelling and Control of The PV Power System Dedicated to The Greenhouse for Reduced Energy Consumption", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 5, pp. 384–393, 2019. doi: 10.25046/aj040550
81. Jeremias Bravo Tapia, Juan José Rivera Toledo, Francisco Ramos Guzmán, Yoxkin Estévez Martínez, "Transformation of Solar Energy to Electricity with Photovoltaic Systems, Reduction of Electrical Consumption and Installation of LED Lamps in the ITSAO", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 5, pp. 234–242, 2019. doi: 10.25046/aj040529
82. Héctor L. Núñez-Ramírez, Gloria G. Carvalho-Kassar, Freddy C. Brito-Maestre, Yaremi I. Gamboa-Maldonado, Luis A. Santos-Avendaño, Carlelines Gavidia-Toro, Orlando Villarroel-Ramos, Dino Di Rosa-Ulloa, "Low-Cost and Accurate Computational System for Efficiency Measures over Photovoltaic Arrays", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 5, pp. 39–45, 2019. doi: 10.25046/aj040505
83. Ahmed Elsayed ELGebaly, Mohamed Kamal El-Nemr, "Optimized Design of PM Halbach Array Linear Generator for Sea Wave Energy Converters Operate at Maximum Power Transfer", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 4, pp. 440–448, 2019. doi: 10.25046/aj040453
84. Darya Denisenko, Nikolay Prokopenko, Nikolay Butyrlagin, "All-Pass RC-Filters Architecture with Independent Adjustment of the Main Parameters Based on Differential Difference Amplifiers", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 4, pp. 65–72, 2019. doi: 10.25046/aj040409
85. Ishaq Sider, Maher Al-Maghalseh, Zaid Alnather, "Energy Consumption Evaluation of Air Cooled Chiller With Cold Storage System Powered by Photovoltaic Modules", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 235–243, 2019. doi: 10.25046/aj040331
86. Maroua Bouksaim, Yassin Acci, Mohamed Nabil Srifi, "Modeling of Grid-Connected Photovoltaic System Installation in Moroccan Ibn Tofail University", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 150–155, 2019. doi: 10.25046/aj040320
87. Mahmut ÜN, "Transfer Function Analysis of Fractional-Order Three-Dimensional Electrically Coupled Cell Network", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 145–149, 2019. doi: 10.25046/aj040319
88. Fernando Hernández, Roberto Vega, Freddy Tapia, Derlin Morocho, Walter Fuertes, "Early Detection of Alzheimer’s Using Digital Image Processing Through Iridology, An Alternative Method", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 126–137, 2019. doi: 10.25046/aj040317
89. Alexander Vodyaho, Evgeniy Postnikov, Alexander Ekalo, Vasiliy Osipov, Nataly Zhukova, Michael Chervontsev, "Cognitive Systems for Monitoring: Architectural View", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 117–125, 2019. doi: 10.25046/aj040316
90. Hakan Tora, Gursel Karacor, Baran Uslu, "Vowel Classification Based on Waveform Shapes", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 16–24, 2019. doi: 10.25046/aj040303
91. Priyamvada Chandel, Tripta Thakur, "A Novel Rule Based Technique to Detect Electricity Theft in India", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 2, pp. 413–421, 2019. doi: 10.25046/aj040251
92. Ajees Arimbassery Pareed, Sumam Mary Idicula, "A Relation Extraction System for Indian Languages", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 2, pp. 65–69, 2019. doi: 10.25046/aj040208
93. Muhammad Aizat Bin Abu Bakar, Abu Hassan Bin Abdullah, Fathinul Syahir Bin Ahmad Sa’ad, "Development of Application Specific Electronic Nose for Monitoring the Atmospheric Hazards in Confined Space", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 1, pp. 200–216, 2019. doi: 10.25046/aj040120
94. Tan Lay Tatt, Lim Boon Huat, Rosli Muhammad Tarmizi, T. Joseph Sahaya Anand, "Perfect Molding Challenges and The Limitations “A Case Study”", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 489–495, 2018. doi: 10.25046/aj030657
95. Lili Liu, Estee Tan, Zhi Qiang Cai, Xi Jiang Yin, Yongda Zhen, "CNN-based Automatic Coating Inspection System", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 469–478, 2018. doi: 10.25046/aj030655
96. Nam Yoon Kim, Jinsung Cho, and Chang-Woo Kim, "An Improved Cross-Connection Abatement Algorithm with RSSI Using In-Band Magnetic Field Control in Densely Located LC Wireless Charger Environments", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 247–251, 2018. doi: 10.25046/aj030632
97. João Manuel Leitão Pires Caldeira, Vasco Nuno da Gama de Jesus Soares, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar, Joel José Puga Coelho Rodrigues, Ricardo Manuel Valentim Fontes, José Luís Lopes Silva, "iSensA – A System for Collecting and Integrating Sensor Data", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 213–221, 2018. doi: 10.25046/aj030628
98. Tareq Khan, "A Wi-Fi based Architecture of a Smart Home Controlled by Smartphone and Wall Display IoT Device", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 180–184, 2018. doi: 10.25046/aj030623
99. Kristóf Csorba, Ádám Budai, "cv4sensorhub – A Multi-Domain Framework for Semi-Automatic Image Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 159–164, 2018. doi: 10.25046/aj030620
100. Saurin Patel, Rick Walker, "Minimally Invasive, Thermal Energy Based, Cost-Efficient Method to Measure Fluid Flows in Compact Systems", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 454–458, 2018. doi: 10.25046/aj030552