The idea of a smart home is getting attention for the last few years. The key challenges in a smart home are intelligent decision making, secure identification, and authentication of the IoT devices, continuous connectivity, data security, and privacy issues. The existing systems are targeting one or two of these issues whereas a smart home automation system that is not only secure but also has intelligent decision making and analytical abilities is the need of time. In this paper, we present a novel idea of a smart home that uses a machine learning algorithm (Support Vector Machine) for intelligent decision making and also uses blockchain technology to ensure identification and authentication of the IoT devices. Emerging blockchain technology plays a vital role by providing a reliable, secure, and decentralized mechanism for identification and authentication of the IoT devices used in the proposed home automation system. Moreover, the SVM classifier is applied to classify the status of devices used in the proposed smart home automation system into one of the two categories, i.e., “ON” and “OFF.” This system is based on Raspberry Pi, 5 V relay circuit, and some sensors. A mobile application is developed using the Android platform. Raspberry Pi acting as the server maintains the database of each appliance. The HTTP web interface and apache server are used for communication among the Android app and Raspberry Pi. The proposed idea is tested in the lab and real life to validate its effectiveness and usefulness. It is also ensured that the hardware and technology used in the proposed idea are cheap, easily available, and replicable. The experimental results highlight its significance and validate the proof of the concept.

/pdf/an-intelligent-secure-and-smart-home-automation-system-3rffihmcdm.pdf

An Intelligent, Secure, and Smart Home Automation System

This paper describes the dynamic modelling of a system used for extraction of groundwater for irrigation using an alternative source of energy. The system is designed based on data of an existing project in Lalmonirhat, Bangladesh. The system comprises a 38.4 kWp solar photovoltaic array, inverter, AC motor, and pump set, which can discharge a maximum of 1,930 m3 of water per day. MATLAB simulation is performed with two types of energy storage system: (i) electric energy using a battery bank and (ii) stored water in a large water tank. A large battery bank and a transformer are needed in the former one, which turns out as a costly solution. The latter one requires a boost converter and a large water tank to store around 2,000 m3 of water, which is also a costly solution. A combination of both systems yields an efficient and economical solution. The effectiveness of these three systems is compared with conventional diesel engine system.

/pdf/dynamic-modelling-of-a-solar-water-pumping-system-with-1z30ski3xx.pdf

Dynamic Modelling of a Solar Water Pumping System with Energy Storage

The smart home is now an established area of interest and research that contributes to comfort in modern homes. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images. Our work uses a camera to capture images of objects triggered by their motion being detected. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. The design of the mobile application allows a graphical display of the activities in the house. Our work proves that machine learning algorithms can improve home automation system functionality and enhance home security. The work’s prototype was implemented using an ESP8266 board, an ESP32-CAM board, a 5 V four-channel relay module, and sensors.

/pdf/internet-of-things-based-intelligent-smart-home-control-16wbzb3xjc.pdf

Internet of Things-Based Intelligent Smart Home Control System

Infrastructure are at the center of three trends: accelerating human activities, increasing uncertainty in social, technological, and climatological factors, and increasing complexity of the systems themselves and environments in which they operate. Resilience theory can help infrastructure managers navigate increasing complexity. Engineering framings of resilience will need to evolve beyond robustness to consider adaptation and transformation, and the ability to handle surprise. Agility and flexibility in both physical assets and governance will need to be emphasized, and sensemaking capabilities will need to be reoriented. Transforming infrastructure is necessary to ensuring that core systems keep pace with a changing world.

/pdf/infrastructure-resilience-to-navigate-increasingly-uncertain-3onbu7jag1.pdf

Infrastructure resilience to navigate increasingly uncertain and complex conditions in the Anthropocene

Building large-scale IoT applications requires enormous infrastructural support. As infrastructure we understand hardware, software and communication channels necessary to ensure interconnection between various heterogeneous components. Project CPS/IoT Ecosystems explores infrastructural requirements for large-scale applications. The applications are realworld scenarios such as smart parking, smart agriculture or smart buildings. In this paper we explore infrastructural requirements necessary to build modular indoor vertical farming system. The proposed prototype is a service-oriented platform distributed over three scopes of operation: cloud, fog, sensor/actuator.

CPS/IoT Ecosystem: Indoor Vertical Farming System

In the present scenario, availability of power and water are insufficient to satisfy the farmer's requirements. Traditionally, implemented techniques of irrigation are proving to be less futile as these are not good at multitasking different concerns which is a combination of availability of water, sources of energy and timely soil profile analysis. With the merger of automation and the methods of irrigation used earlier, the scope to mitigate issues concerning water and power crisis, is huge. In this paper, an Internet of Things based solar powered smart irrigation system with monitoring and control features, is designed and implemented. The sensor enabled proposed model of smart irrigation system along with its Android Application and ESP8266 as its main controller is successfully implemented and the results of the implemented are presented.

Solar Powered Smart Irrigation System Using Internet of Things

Internet of Things (IoT) is a fast emerging concept which is going to affect our life style in a big way. There is a need to include IoT in the under graduate engineering curriculum following the global trend for outcome based education. In this paper, details of various stages of development of an introductory laboratory based on IoT are presented. It starts with tackling the challenges and designing laboratory experiments with limited resources available. Project based learning approach is adopted to develop this laboratory through students. The students' feedback on learning experience is also included.

Development of an Internet of Things (IoT) Based Introductory Laboratory for Undergraduate Engineering Students

The concept of automation coupled with advancement in technology and Android based smart phones have resulted in refined and smart lifestyles. When automation as a concept gets implemented via internet of things (IoT) which is concerned with accumulation /aggregation of connectivity, it gives rise to a smarter home network. In this paper, an IoT based prototype of a smart home automation is designed and implemented. The proposed prototype smart home system along with its Android App and ATmega16 as its main controller is successfully implemented and the results of the implementation are presented.

Design and Implementation of an Internet of Things based Prototype for Smart Home Automation System

Objective: To evaluate the nootropic activity of methanolic extract of pre-shodhit and shodhit Semecarpus anacardium (SA) nuts and to observe the effect of shodhana on nootropic activity of SA. Methods: Spatial learning and working memory was considered for evaluation. The parameters used were spontaneous alternation behavior (Y-maze), number of correct responses (radial maze), and transfer latency in day 1 (elevated plus maze). Scopolamine, an anticholinergic drug, was used to induce cognitive deficit. % inhibition of acetylcholine esterase (AChE) was measured in vitro. Results: Both pre-shodhit and shodhit drug reversed the scopolamine-induced a decrease in percentage spontaneous alternation behavior in Y-maze and number of correct responses in radial maze. Scopolamine-induced increase in transfer latency in elevated plus maze was significantly decreased by pre-shodhit drug only. Shodhit drug has no significant effect on transfer latency. Both pre-shodhit and shodhit drug showed dose-dependent inhibition of AChE activity in vitro. Pre-shodhit drug showed a more nootropic activity than shodhit drug. Conclusion: Methanolic extract of the nuts of S. anacardium possesses nootropic activity which may be attributed to inhibition of cholinesterase activity. Shodhana of the nuts decreases nootropic activity. Keywords: Semecarpus anacardium, Acetylcholine esterase, Shodhana, Nootropic.

/pdf/shodhana-decreases-nootropic-activity-of-semecarpus-41eksyi0gs.pdf

Shodhana decreases nootropic activity of semecarpus anacardium

Multi level inverters (MLI) are being preferred over conventional two level inverters as the former topologies have minimum harmonic distortion, electromagnetic interference and higher DC link voltages. On the other hand, these devices have some inherent drawbacks like increased number of switches, complicated control techniques and requirement of many voltage sources. A conventional topology uses 12 switches for a 7-level MLI design. In this paper, a modified reduced switch topology based 7-level inverter is proposed which require only 7 or 6 switches. Design, simulation and comparison of 7-level 7switch, and 7-level 6-switch inverters are carried out in MATLAB/SIMULINK environment. A hardware implementation of the above topologies for validation is also included.

Kshirod Kumar Rout

Papers

Solar Powered Smart Irrigation System Using Internet of Things

Development of an Internet of Things (IoT) Based Introductory Laboratory for Undergraduate Engineering Students

Design and Implementation of an Internet of Things based Prototype for Smart Home Automation System

Shodhana decreases nootropic activity of semecarpus anacardium

A Modified 7-Level Reduced Switch Symmetrical Inverter