International Journal of Computer and Applications

It is estimated that the world will need to double its energy supply by 2050. Nanotechnology has opened up new frontiers in materials science and engineering to meet this challenge by creating new materials, particularly carbon nanomaterials, for efficient energy conversion and storage. Comparing to conventional energy materials, carbon nanomaterials possess unique size-/surface-dependent (e.g., morphological, electrical, optical, and mechanical) properties useful for enhancing the energy-conversion and storage performances. During the past 25 years or so, therefore, considerable efforts have been made to utilize the unique properties of carbon nanomaterials, including fullerenes, carbon nanotubes, and graphene, as energy materials, and tremendous progress has been achieved in developing high-performance energy conversion (e.g., solar cells and fuel cells) and storage (e.g., supercapacitors and batteries) devices. This article reviews progress in the research and development of carbon nanomaterials during the past twenty years or so for advanced energy conversion and storage, along with some discussions on challenges and perspectives in this exciting field.

Carbon Nanomaterials for Advanced Energy Conversion and Storage

Due to the current structure of digital factory, it is necessary to build the smart factory to upgrade the manufacturing industry. Smart factory adopts the combination of physical technology and cyber technology and deeply integrates previously independent discrete systems making the involved technologies more complex and precise than they are now. In this paper, a hierarchical architecture of the smart factory was proposed first, and then the key technologies were analyzed from the aspects of the physical resource layer, the network layer, and the data application layer. In addition, we discussed the major issues and potential solutions to key emerging technologies, such as Internet of Things (IoT), big data, and cloud computing, which are embedded in the manufacturing process. Finally, a candy packing line was used to verify the key technologies of smart factory, which showed that the overall equipment effectiveness of the equipment is significantly improved.

Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges

Analysis and comparison of different PV array configurations under partial shading conditions

Dominance square based array reconfiguration scheme for power loss reduction in solar PhotoVoltaic (PV) systems

The maximizing lifetime of Barrier coverage in wireless sensor network has attracted researchers in recent past. In barrier coverage applications it is essential to prolong the lifetime of sensor networks which guarantees extended operating lifetime of the overall network. In this paper, we propose a novel Tell Neighbor Algorithm (TNA), which increases the operating lifetime of the overall network. Simulation results show that the lifetime obtained by TNA is better than some of the already existing state-of-art algorithms. Lifetime obtained by TNA is doubled when compared already existing algorithms.

/pdf/maximizing-lifetime-of-barrier-coverage-wireless-sensor-3mocqe61xr.pdf

Maximizing Lifetime of Barrier Coverage Wireless Sensor Network with Tell Neighbor Algorithm

Home Automation System Using DTMF

The real-time smart monitoring with intelligence highly gained signi ﬁ cant attention for enhancing the productivity of the crop. Currently, IoT generates a lot of real-time data from the sensors, actuators, and identi ﬁ cation technologies. However, extracting the meaningful insights from the data is necessary for realizing the intelligent ecosystem in agriculture. Based upon the previous studies, it is also identi ﬁ ed that the limited studies have merely implemented machine learning (ML) on real-time data obtained through customized hardware with dedicated server. In this study, we have proposed a customized hand-held device that enables to deliver recommendations to the farmer on the basis of real-time data obtained through IoT hardware and ML. A three-layer structure is proposed in the study for realizing custom hardware with 2.4GHz ZigBee and IoT sensors for the data acquisition, communication, and recommendation. As a part of real-time implementation, the calibration of the sensors is processed to form a real-time dataset with precision. The study evaluated four ML models and concluded that XGBoost has shown a better accuracy on the proposed dataset. The XGBoost recommended the crop based on selected parameters. The developed hand-held device can be customized with advance features with crop recommendations.

Agriculture Field Automation and Digitization Using Internet of Things and Machine Learning

The present review article represents the scope of different lead (Pb)-free hybrid halide Perovskite solar cells (PSC) for photovoltaic (PV) applications. Research on lead-free material is emerging mainly to identify the alternatives of lead in the Perovskite solar cells. Several homovalent (Sn2+, Ge2+, Cu2+) and heterovalent (Sb3+, Bi3+, Ti4+) materials have good physical properties to replace the lead content in the absorbing material compound. However the power conversion efficiency (PCE, %) is not higher as compared to lead based material. This review article focuses on the characteristics, material properties, stability and performance of the different Pb-free materials as absorbing layer in the Perovskite solar cells.

Recent advances in lead-free based perovskite solar cells on optoelectronic properties, stability and economic feasibility

This book provides basic knowledge of the programming and interfacing of devices with IoT modem and programming. The aim is to explain the basic steps to understand the IoT and its application in agriculture field. It will serve be a reference book for postgraduate and undergraduate Engineering students. Students from Electronics, Electrical, Mechatronics, Robotics, Mechanical, Computer science can use the book for their projects and research. This book is based entirely on the practical experience of the authors while undergoing projects with the students and industries. This book is co-published with NIPA. Taylor and Francis does not sell or distribute its print and electronic editions in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. 

Sushabhan Choudhury

Papers

Maximizing Lifetime of Barrier Coverage Wireless Sensor Network with Tell Neighbor Algorithm

Home Automation System Using DTMF

Agriculture Field Automation and Digitization Using Internet of Things and Machine Learning

Recent advances in lead-free based perovskite solar cells on optoelectronic properties, stability and economic feasibility

Internet of Things (IoT) Enabled Automation in Agriculture