Deployment of 5G Technology for Sustainable Precision Agriculture in Ibaji Local Government Area of Kogi State | Chapter 3 | New Horizons of Science, Technology and Culture Vol. 7

 

The integration of 5G technology into smart and sustainable agriculture has the potential to revolutionise agricultural productivity and enhance food security in the Ibaji Local Government Area (LGA) of Kogi State, Nigeria. Food insecurity and malnutrition continue in the region because of outdated farming methods. These make food production susceptible to unpredictable rainfall, limited access to modern agricultural technologies, and unprofitable yields. Although 5G-enabled precision agriculture has been widely explored, only a few studies integrate 5G deployment with structured security threat analysis frameworks, such as STRIDE, particularly in smallholder farming contexts. This study assessed the potential of 5G-enabled Internet of Things (IoT) technologies for real-time tracking and automated control of resource (input) optimisation to improve farm resource (input) management and profitability. Using a mixed-method approach that included agricultural field surveys of local farmers and simulations of 5G sensors as agricultural technology for the Ibaji region in Kogi State, Nigeria, the Ibaji precision agriculture system was designed. The study analyses two primary use cases: Sensor-Based Monitoring and Automated Resource Management. For Field Surveys, 50 local farmers were surveyed to understand the primary agricultural problems and to assist in the validation of sensor placement. Additionally, a simulation-based system design was developed using Python to model 5G-connected sensors and actuators for real-time monitoring of soil moisture, nutrients, and pH levels. Results revealed that 5G technology for resource control and farm practice optimisation led to improved agricultural yields by 20% and resource management by 15%, demonstrating the potential of modern technology to alleviate food security challenges and resource poverty in the region. This study concludes that a basic 5G-enabled sensing and actuation stack, secured with minimal but critical controls, can improve yields and reduce input use in a resource-constrained smallholder setting such as Ibaji.

 

 

Author(s) Details

Felix Ayegba Sani
Computer Science Department, The Federal Polytehnic, Idah, Kogi State, Nigeria.

 

Ugbedeojo Musa
Computer Science Department, The Federal Polytehnic, Idah, Kogi State, Nigeria.

 

Please see the book here :- https://doi.org/10.9734/bpi/nhstc/v7/6963

Smart Gardening System Using Microcontroller and Smart Application| Chapter 7 | Intelligent IoT Systems: From Research to Real-World Solutions

 

The Smart Gardening System represents an IoT-driven initiative designed to make plant maintenance easier and more effective by handling watering automatically. It relies on a soil moisture sensor to track moisture levels in the soil continuously. If the soil gets too dry—say, below 30% moisture—the sensor alerts the Arduino Uno microcontroller, which then switches on a water pump using a relay module. The pump stops once the soil hits an optimal level, like 60%, to avoid wasting water or drowning the roots. Core parts include the Arduino Uno, soil moisture sensor, relay module, water pump, and a separate power source. To make things user-friendly, we have added a basic web page built with Flask that shows live updates on soil moisture and whether the pump is running or not, so people can check in from anywhere online. During tests, the setup responded in less than a second, with the sensor hitting 95% accuracy across different soils, and it cut water use by about 40% compared to doing it by hand. This approach cuts down on manual work, stops plants from getting too much or too little water, and helps them grow stronger. It's especially handy for folks with packed schedules or who travel a lot. In the end, it makes gardening more sustainable by saving resources and effort.

 

 

Author(s) Details

Sumit Singha Chowdhury
Department of Master of Computer Application, Acharya Institute of Technology, Bengaluru, Karnataka, India.

 

Barsha Mallick
Department of Master of Computer Application, Acharya Institute of Technology, Bengaluru, Karnataka, India.

 

Manish Kumar Thakur
Department of Master of Computer Application, Acharya Institute of Technology, Bengaluru, Karnataka, India.

 

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH7

Agrosense: IOT-Based Smart Vegetable Gardening System|Chapter 6 | Intelligent IoT Systems: From Research to Real-World Solutions

 

Greenhouse farming needs precise monitoring to guarantee healthy plant growth, while conventional methods are cumbersome, inexact, and not amenable to steady-state operation. This study outlines an Internet of Things (IoT)-based vegetable garden monitoring system that automatically controls irrigation, climate, and plant disease in a greenhouse. The system incorporates an LDR light sensor, ESP32-CAM, soil moisture sensor, and DHT11 temperature-humidity sensor controlled by an ESP8266. A motor pump is activated when the soil moisture is less than the threshold value; temperature and humidity are controlled by a fan, while light is provided through an LED when light intensity is low. At specified time epochs, the ESP32-CAM shoots plant pictures that are analysed through a Python-based deep learning algorithm to determine five plant health classes: yellow leaves, curled leaves, leaf spot, white fly infestation, and healthy. A web page presents sensor readout in real time as well as disease classification outcome. Experimental validation indicates classification accuracy of 94.6 %, ±2°C accuracy in temperature regulation, ±5% in humidity control, and 92% accuracy in irrigation. Against previous works that employed IoT to automate greenhouse farming, this solution is not only superior in control accuracy but also incorporates automatic disease diagnosis. Despite limitations due to internet reliability as well as dataset size, the solution provides insights into how IoT, as well as AI, can minimize manual intervention, facilitate early detection, as well as, promote sustainable farming.

 

 

Author(s) Details

Hanamant R Jakaraddi
Department of MCA, Acharya Institute of Technology, Bangalore-560107, India.

 

Hridhik Hareendran
Department of MCA, Acharya Institute of Technology, Bangalore-560107, India.

 

Sridevi G
Department of Computer Applications, Acharya Institute of Graduate Studies, Bangalore-560107, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH6

IoT-Enabled Smart Aquarium System for Automated Feeding and Real-time Monitoring | Chapter 4 | Intelligent IoT Systems: From Research to Real-World Solutions

 

There are significant requirements for environmental monitoring and fish feeding logs when managing an aquarium, which can also be tedious and error-prone for the caregiver/technician. The rapid adoption of Internet of Things (IoT) technologies opens up exciting new opportunities for aquarium management by automating tasks that will allow the environment to remain stable for the aquatic life. This chapter discusses the design and evaluation of a Smart Aquarium System that can automate fish feeding and monitor temperature, pH, turbidity, and water level, as well as real-time connectivity via the cloud. An ESP32-CAM module was also integrated into the system, which transmits live video and images, so fish and how the system is functioning can be observed remotely. The Smart Aquarium system was tested under various operating conditions to evaluate accuracy, responsiveness, and reliability. The results showed it had a feeding accuracy of 96.4%, temperature maintained to a range of ±0.5 °C, pH was reliably detected in the 6.0–8.0 range, turbidity results were reported in NTU units, and the water level stabilised within a range of ±1 cm, respectively. Cloud-based data transfer was accomplished with an average latency of less than 200 ms, which supported effective real-time cloud and local visualisation and control. Safety procedures, such as dry-run prevention for a pump and fault-detection for sensors, were established to enhance reliability. Overall, the results suggest that IoT-based smart aquariums indicate a reduction in manual workload, improve user management of aquatic health and potentially be a low-cost tool for users, including aquaculture operators and hobbyists.

 

 

Author(s) Details

 

Hanamant R Jakaraddi
Department of MCA, Acharya Institute of Technology, Bangalore- 560107, India.

 

Anurag O
Department of MCA, Acharya Institute of Technology, Bangalore- 560107, India.

 

Vivek R Venkatesh
Department of Computer Applications, Acharya Institute of Graduate Studies, Bangalore-560107, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH4

IOT-Based Smart Energy Management System for Real-Time Monitoring and Automation | Chapter 2 | Intelligent IoT Systems: From Research to Real-World Solutions

 

In present days, energy consumption is becoming a major concern for individuals, businesses, and agriculture. Inefficient energy consumption contributes to environmental degradation by raising electricity bills and increasing reliance on non-renewable resources. This approach gives a design and implements an IoT-based Smart Energy Management System for real-time monitoring, predictive automation, and cloud-based control of electrical appliances in smart homes. The system was created using various sensors to track voltage, current, temperature, occupancy and light. Real-time automation was obtained using relay modules and a servo motor for curtain automation. Firebase Realtime Database was utilised for cloud storage, control, and predictive data retrieval. Energy consumption was calculated in kilowatt-hours based on voltage and current values. Manual, schedule-based, and predictive override were implemented. The system effectively monitored energy consumption and reduced power levels by 18%. It automatically shut down equipment when idle or in accordance with pre-scheduled occupancy estimates. The system responded in real-time to sensor inputs and user-scheduled events. Power telemetry and daily logging were always synchronised with Firebase to enable smooth cloud updates and user interaction. The proposed system offers a safe, scalable, and intelligent home energy management system for the future through the use of IoT sensors and cloud technology to enable automation, predictive control, safety, and future-proof compatibility with new smart grid infrastructure for improved sustainability and operational efficiency.

 

 

Author(s) Details

Hanamant R Jakaraddi
Department of MCA, Acharya Institute of Technology, Bangalore-560107, India.

 

Amarnath C K
Department of MCA, Acharya Institute of Technology, Bangalore-560107, India.

 

Ranjana K K
Department of Computer Applications, Acharya Institute of Graduate Studies, Bangalore-560107, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH2

 

Smart Water Management Using IoT: An Integrated Approach to Conservation and Automation | Chapter 1 | Intelligent IoT Systems: From Research to Real-World Solutions

 

This chapter describes a complete IoT system for domestic and small-scale smart water management that integrates three capabilities: non-contact tank level monitoring; flow-based sealed leak detection with occupancy awareness; and automatic rainwater harvesting. A Wi-Fi-enabled microcontroller integrates sensor inputs and manages local alerts and actuators; a cloud dashboard (Blynk) provides a real-time view, notifications and remote control. This modular, inexpensive system is designed for ease of installation on standard rooftop/storage tanks while allowing user-defined thresholds and operational modes (Home/Away) to reduce noticeable false alarms. The architecture emphasises affordability and practicality, ensuring that it can be adopted even in resource-constrained settings. The design philosophy focuses on simplicity, reliability, and long-term usability. Bench test results in a simulated home environment are illustrative of a reliable system: level estimation remained within ~5% of manual level measurement; leak events prompted action within a remarkable time when Away mode was on; rain-induced lid actuation completed in a matter of seconds. The local buzzer/LED alerts perform as required during a network failure and restore automatically when service is restored. The integration of monitoring, anomaly detection, and harvesting into a single architecture minimises manual engagement, mitigates avoidable loss, and encourages more sustainable use of both stored and harvested water. In addition to benefits for the individual household, this approach is also aligned with larger sustainability objectives. It permits data-driven conservation and creates a retrofit pathway for legacy tanks. This chapter describes the design, implementation, and evaluation of the prototype, practical considerations, future upgrade paths (e.g., predictive analytics, implementation of a backup power source for the actuators, pathway to scaling functionality to multi-tank scenarios, or community-based designs) to facilitate real-world implementation and future research investigations.

 

 

Author(s) Details

Sumit Singha Chowdhury
Department of MCA, Acharya Institute of Technology, Soladevanahalli, Bengaluru, India.

 

Rakhshita B
Department of MCA, Acharya Institute of Technology, Soladevanahalli, Bengaluru, India.

 

K Ramesh Adiga
Department of MCA, Acharya Institute of Technology, Soladevanahalli, Bengaluru, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-94-5/CH1

IoT-Enabled Health Monitoring System for Elderly Care | Chapter 6| Scientific Research, New Technologies and Applications Vol. 1

The goal of this project is to create and implement a complete hardware model for ongoing health monitoring. Through the use of specialized sensors, the system monitors critical health factors like blood pressure, temperature, sweat, oxygen saturation, heart rate, and patient falls. Medical practitioners and the patient's family can access the information through the wireless transmission of data points to a central database using Internet of Things technology. The research entailed designing a user-friendly data access interface, establishing the wireless transmission protocol, and choosing and integrating the proper sensors. With real-time vital sign monitoring available from anywhere, the system is specially designed with senior patients in mind. It also has an emergency alert mechanism that will swiftly contact the appropriate authorities. This research facilitates effective patient monitoring and aids healthcare professionals in overseeing several patients.

 

Author (s) Details

S. Kalaivani
Department of ECE, BSA Crescent Institute of Science and Technology, Chennai, India.

 

R. Mahalakshmi @ Isakki
Department of ECE, BSA Crescent Institute of Science and Technology, Chennai, India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/srnta/v1/1814

 

Transforming Indian Petro Retail: Enhancing Customer Experience through IoT and AI Solutions | Chapter 5 | Scientific Research, New Technologies and Applications Vol. 10

This study uniquely explores the applicability and impact of deploying an IoT and AI-driven solution, specifically a CCTV-based system, to enhance customer experience at a fuel retail outlet in India. The solution leverages IoT and AI technologies to capture customer details, ensure adherence to safety protocols, and monitor service delivery standards. By adopting a technology-led approach, the initiative aims to improve service efficiency, enhance customer satisfaction, and elevate overall customer experience.

The experiment was conducted at a fuel station in Mumbai from August to October 2020. During this time, data was systematically collected and analysed to assess the solution's effectiveness. The findings demonstrate the utility of an IoT and AI system in identifying and tracking customer behaviour and movements on the forecourt. The solution proved particularly effective in enforcing safety protocols, contributing to a heightened sense of security among customers, which, in turn, positively influenced their satisfaction levels.

The research highlights several benefits of implementing IoT-based solutions in petro retail. These include improved customer identification, enhanced operational efficiency, and increased customer acquisition and retention. The integration of such technologies not only boosts customer satisfaction but also contributes to a more seamless and engaging customer experience, ultimately driving higher sales performance.

This study represents a pioneering effort to explore the application of IoT and AI solutions in the Indian petroleum retail sector. It underscores the potential of these technologies to transform service delivery and customer interactions, setting a foundation for further research and innovation in this field.

 

Author (s) Details

 

Santanu Purohit
School of Business, University of Petroleum & Energy Studies, Dehradun, India.

 

Sujoita Purohit
Mohanlal Sukhadia University, Udaipur, Rajasthan, India.

 

Arvind Kumar Jain
School of Business, University of Petroleum & Energy Studies, Dehradun, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/srnta/v10/3554

Study of an Innovative Approach to IoT Based Human Activity Recognition | Chapter 19 | Leading the Charge: A Guide to Management, Entrepreneurship and Technology in the Dynamic Business Landscape Edition 1

Recognizing human activities is vital for numerous contemporary applications rooted in the Internet of Things (IoT) framework, spanning from the creation of intelligent video surveillance setups to the advancement of robotic assistants for the elderly. Recently, there has been significant exploration into machine learning algorithms to enhance the recognition of human activities. Despite these research endeavors, there remains a notable dearth of studies focusing on efficiently recognizing complex human activities, particularly those involving transitions, and no research has been conducted to assess the impact of noise in training data on algorithm performance. This paper addresses these gaps by presenting an innovative activity recognition system centered on a neural classifier with memory capabilities, designed to optimize the classification of both transitional and non-transitional human activities. Utilizing unobtrusive IoT devices such as accelerometers and gyroscopes integrated into widely-used smartphones, the system effectively identifies human activities [1,2]. The key feature of the proposed system lies in leveraging a neural network augmented with short-term memory to retain information about preceding activities' characteristics. Experimental validation demonstrates the reliability and accuracy of the proposed system compared to state-of-the-art classifiers, highlighting its robustness in handling noisy data. Human Activity Recognition (HAR) is essential for various modern applications within the Internet of Things (IoT) framework, from developing intelligent video surveillance systems to enhancing robotic assistants for the elderly. Despite significant advancements in machine learning algorithms for HAR, there is a notable lack of research on effectively recognizing complex human activities, particularly those involving transitions, and assessing the impact of noise in training data on algorithm performance. This paper addresses these gaps by presenting an innovative activity recognition system centered on a neural classifier with memory capabilities. Designed to optimize the classification of both transitional and non-transitional human activities, the system employs unobtrusive IoT devices such as accelerometers and gyroscopes integrated into widely used smartphones [1,3]. A key feature of the proposed system is the utilization of a neural network augmented with short-term memory to retain information about preceding activities' characteristics. Experimental validation demonstrates the system's reliability and accuracy compared to state-of-the-art classifiers, emphasizing its robustness in handling noisy data.

 

Author (s) Details

 

Motashim Rasool
Integral University, India.

 

Rizwan Akhtar
Integral University, India.

 

Uvais Ahmad
Integral University, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48859-98-3/CH19

Aqua Kit: A Kit for Efficient Freshwater Fish Farming – A Comprehensive Sensor-Based Approach | Chapter 13 | Leading the Charge: A Guide to Management, Entrepreneurship and Technology in the Dynamic Business Landscape Edition 1

Fish farming and aquaculture have been practiced for hundreds of years, and Asia’s country has shared approximately 55% of global production.  In recent years, the authorization body has noticed a significant drop in fish farming in fresh water, like ponds, and lakes, and also several unclarities among people on how to take care of fish in artificial aquatic resources. The main causes of that include inadequate optimization a poor understanding of and culture surrounding fisheries a weak approach to fishing a shortage of personnel and a dearth of reliable databases pertaining to aquatic and fisheries resources, weak approach to fisheries, inadequate manpower, water pollution, poor optimization, and not adequate good fisheries knowledge and culture. The integration of Internet of Things (IoT) technology has revolutionized the realm of freshwater fish farming by providing a sophisticated and real-time monitoring system. This paper proposes an innovative approach to enhancing the aquaculture industry through the utilization of various sensors and IoT devices. By continuously monitoring water quality parameters and the well-being of aquatic life, this approach aims to optimize the farming process, mitigate risks, and ensure a sustainable environment for freshwater fish. The proposed solution may cover all of the above aspects to build a healthy fisheries culture and easily connect aqua research and development to continue monitoring to the ground level, it will also help to maintain a proper database to build better aquaculture, maintain the sustainability of nature and aquaculture. The system will be a smart machine learning (deep learning) and Internet of Things (IoT) based system that can detect oxygen, temperature, Ph level, ammonia, water overflow, fish disease, and many more and store the data as (big data) also manage to have user-friendly communication with as well as higher authorities.

 

Author (s) Details

 

Sumit Singha Chowdhury
Department of MCA, Acharya Institute of Technology, Bangalore, India.

 

Ratnakirti Roy
Department of MCA, Acharya Institute of Technology, Bangalore, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48859-98-3/CH13

Smart Intelligent Infant Cradle | Chapter 23 | Innovative Solutions: A Systematic Approach towards Sustainable Future

Aim: The aim of an intelligent infant cradle could be to provide a safer, more comfortable, and convenient environment for infants while also integrating intelligent features that can monitor the baby's health, modify the surroundings, and provide caregiver feedback.

Study Design: This study aims to evaluate the effectiveness, safety, and user satisfaction of an intelligent infant cradle compared to traditional cradles. Infants aged 0-6 months and their caregivers will be randomly assigned to either the experimental (intelligent cradle) or the control group (traditional cradle). Outcome measures include infant sleep quality, incidence of sleep-related issues, caregiver satisfaction, safety, parental stress levels, and infant developmental outcomes. Data will be collected through questionnaires, interviews, observations, and objective measurements. Statistical analysis will compare outcomes between groups. Ethical considerations include obtaining informed consent and approval from institutional review boards. Limitations may include sample bias and reliance on self-reported data.

Place and Duration of Study: Department of Electronics And Communication Engineering, Pes Institute Of Technology And Management (PESITM) Shimoga, From Sept 2023.

Methodology: The proposed iot-based smart cradle utilizes a raspberry pi model 3 b+ board, camera module, sound sensor, lm35 temperature sensor, and wet sensor. A DC motor swings the cradle upon detecting the baby's cry through the sound sensor. A melody tune plays simultaneously to soothe the baby. Caregivers can remotely control the swing via IoT server buttons. The LM35 temperature sensor activates a fan when humidity exceeds a set level. A wet sensor alerts caregivers to change the baby's diaper. Additionally, a camera provides real-time monitoring of the baby's sleep.

Results: This project proposes an innovative automatic caretaker room for infants, designed to address the time and energy constraints faced by busy parents. The primary goal is to cater to the needs of working individuals who struggle to find sufficient time for proper baby care. The entire room is equipped with sensors and a microprocessor, allowing it to autonomously sense and respond to the baby's activities. This approach eliminates the need for constant manual checks by parents, enabling them to save valuable time and energy. The system, driven by sensors, connected to the microprocessor, continuously monitors both room conditions and the baby's activities. It operates based on predefined conditions, ensuring parents receive real-time information about their baby without physical presence. The collected data is readily accessible, providing a comprehensive overview of the baby's status, and notifications are sent as needed. In summary, this automated caretaker room offers a practical and efficient solution for busy parents, allowing them to stay informed and connected with their baby's well-being while optimizing their resources.

Conclusion: The advanced features of the baby monitoring system offer a comprehensive solution for working parents, addressing various aspects of infant care and safety. From real-time video monitoring to proactive alerts for emergencies and environmental conditions, this system not only provides peace of mind to parents but also creates a secure and comforting environment for the baby. By seamlessly integrating technology into childcare, the system enables working parents to balance their professional commitments while staying connected and responsive to their baby's needs, ultimately fostering a sense of freedom and reduced stress in their daily lives.

 

Author (s) Details

C. Chandana
Department of ECE, PES Institute of Technology and Management, Shivamogga, India.

 

S.P. Kavana
Department of ECE, PES Institute of Technology and Management, Shivamogga, India.

 

M. Vanishree
Department of ECE, PES Institute of Technology and Management, Shivamogga, India.

 

Ranjith
Department of ECE, PES Institute of Technology and Management, Shivamogga, India.

 

S.R. Srilakshmi Nayaka
Department of ECE, PES Institute of Technology and Management, Shivamogga, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-49238-47-3/CH23

IoT and Healthcare: An Overview | Chapter 13 | Innovative Solutions: A Systematic Approach towards Sustainable Future

This report is focused on Internet of Things or IoT's impact on healthcare, emphasizing the need for adaptation as IoT solutions expand. This paper aims to achieve global connectivity between IoT and medical environments, addressing challenges for professionals and transforming healthcare through efficient integration. Some applications of IoT in healthcare include remote patient monitoring, self-maintenance medical devices, and telemedicine with virtual visits, all of which enhance patient care and increase the access of healthcare services. 5G networks are going to play a major role in order to enable widespread adoption of IoT and improve the patient monitoring system in healthcare. The extensive study came up with a proposal for healthcare industry with future readiness with the use of IoT.

 

Author (s) Details

 

Arpita Santra
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India.

 

Sandhya Pattanayak
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India.

 

Sangita Roy
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India.

 

Aditi Paswan
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India.

 

Soubhik Saha
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India

 

Saikat Dholey
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India.

 

Simran Prasad
Department of ECE, Narula Institute of Technology, 81, Nilgunj Road, Kolkata – 700109, India.

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-49238-47-3/CH13

An Evaluation Approach towards Dynamic Memory Balancing in IoT Applications Through Machine Learning Algorithms | Chapter 10 | Science and Technology: Developments and Applications Vol. 4

The term consistent would be more able to coin as the Internet of Things to be the most encouraging innovation which has developed numerous inward branches like the Web of Clinical Things, etc. IoT arranges actuators with comparing propels for giving accommodating information yield. The part of the actuator gadget shifts concerning the application and environment it is sent for. More modest activating machines have a lesser useful cutoff as a result of their limited memory district. Overseeing or keeping up with of capacity of the IoT-based parts is critical for optimizing processing speed and ensuring the responsiveness of selected devices. The composition upholds the Priority Based Memory or Storage Balancing (PBMB) method in the effective treatment of capacity to chip away at the speed of response of the actuator devices. The memory-changing arrangement depends on progressive computer-based intelligence estimation that separates a periodic approach to acting the gadget in managing requests. Considering the assessment, the available memory space is assigned and freed for moving requests and taking care of information. The developing experience is persuaded through time-subordinate transmission direct discernments. The used memory leads procedure works in an adaptable way for evolving time-fundamental and non-surrender tolerant applications by limiting putting away and access delay at the gadget level. The proposed procedure is planned to confine memory abuse, and association delay and to collect the sales taking care of rates.

 

Author (s) Details

S. M. Shamsheer Daula
Department of ECE, G Pulla Reddy Engineering College (A), JNTUA, Kurnool, Andhra Pradesh-518007, India.

 

G. Amjad Khan
Department of ECE, G Pulla Reddy Engineering College (A), JNTUA, Kurnool, Andhra Pradesh-518007, India.

 

G. Ramesh
Department of ECE, G Pulla Reddy Engineering College (A), JNTUA, Kurnool, Andhra Pradesh-518007, India.

 

M. Madhusudhan Reddy
Department of ECE, G Pulla Reddy Engineering College (A), JNTUA, Kurnool, Andhra Pradesh-518007, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/stda/v4/3879 

Assessment of Voice Controlled Industrial Parameters Monitoring and Controlling System: An Update | Chapter 10 | Theory and Applications of Engineering Research Vol. 7

 

In this paper, we are proposing a system that allows humans to monitor and control Industry motor automatically. Its advantage is that if suddenly any system is not working properly in the industry and there is no worker available near the system then it will automatically perform certain actions accordingly. Through the Internet of Things, we may operate our appliances from any location in the globe. In the industrial sector, worker irresponsibility is frequently the cause of accidents, and there are certain hazardous places where workers are unable to perform their jobs. Voice-controlled Industrial parameters monitoring and controlling system are used in the risky areas of Industries usually in power plants where there are high noise level and pollution to avoid accidents. Here an induction motor speed, temperature, pressure, etc are monitored and controlled to avoid damage to the motor. These all the parameters are going to monitor and controlled automatically. In this paper, Google-Assistant and Adafruit IO server are used for monitoring and controlling. By using this system the workers can monitor and control Industrial appliances and problems occur in Industries where workers not able to go and work are overcome. By using this system, we can monitor Industrial appliances and its parameters on the Adafruit IO server and control it by using voice commands through Google Assistant.

Author(s) Details:

Saurabh Sathawane,
Department of Electronics and Telecommunication, Yeshwantrao Chavan College of Engineering Nagpur, India.

A. D. Belsare,
Electronics and Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, India.

Vaibhav Deshpande,
Syslogyx Technologies Pvt. Ltd., Nagpur, India.

Snehal Warade,
Department of Electronics and Telecommunication, Yeshwantrao Chavan College of Engineering Nagpur, India.

Tanay Thakre,
Department of Electronics and Telecommunication, Yeshwantrao Chavan College of Engineering Nagpur, India.

Please see the link here: https://stm.bookpi.org/TAER-V7/article/view/13729

Self-Sustained E-Toilet System Using IOT | Chapter 9 | Contemporary Perspective on Science, Technology and Research Vol. 2

Now, the e-Toilet system that exists are run manually. Seeing, current situation of Covid-19 and Omicron skilled is a risk to use such manual whole. So, by considering health and cleanliness factor we are trying to present a solution that can solve issues related to cleanness by using a electrical system. e-Toilets are self-contained, self-cleansing, user-friendly, unmanned, electronic toilet cauldrons installed in public places. The whole unit is make sense of stainless steel. E-Toilets have sensors to introduce automatic functions.E-Toilet is a coin conducted pay Toilet. Diversified sensors are used to automate the whole structure. The whole sensor dossier is provided to authorize individual through IoT. The waste water from the system is before supplied to the secret tank through which it goes for cleansing purpose. The major aim of wastewater situation is to remove as much of the postponed solids as possible before the staying water, called discharge, is discharged back to the environment.Wastewater Plant is secondhand here, that will treat the release water coming out from e-Toilet method and make the reusable water that will further used for diversified purposes like for Agriculture purpose. So in this way we can control plenty diseases that are happening because of wastewater.

Author(s) Details:

S. S. Gurav,
ETC Department, Sharad Institute of Technology, College of Engineering, Yadrav, India.

V. V. Khandare,
ETC Department, Sharad Institute of Technology, College of Engineering, Yadrav, India.

G. A. Chougule,
ETC Department, Sharad Institute of Technology, College of Engineering, Yadrav, India.

Please see the link here: https://stm.bookpi.org/CPSTR-V2/article/view/12906

Localization for IoT Based Systems Using UWB | Chapter 2 | Contemporary Perspective on Science, Technology and Research Vol. 2

The refined, cutting-edge low capacity, low cost Wi-Fi technologies of today create the Internet of Things (IOTs) a important platform. IOT uses are being used on an increasing base in a variety of contexts, containing smart factories, smart centers, smart industries, and smart homes. Gaining a suitable level of precision and veracity in localizing the person, object, or device is critical for each of these requests. In IOT, every gadget is related to every other device through the WWW. One habit to classify localization is as measurements of extent, angle, distance, etc. Numerous wireless sciences, including high frequency identification (RFID), Bluetooth low strength (BLE), WiFi, and ultra-wideband (UWB), are utilized in Cyberspace of Things (IOT) schemes to achieve dependable localization. It has happened discovered that UWB plays a crucial function. Because UWB has a wide repetitiveness range (3.1GHz–10.6GHz), a low duty phase (maximum on time 5ms and off time 38ms), extreme accuracy of ranging (cm), uses very narrow pulses (ns to localize), can travel obstacles, can prevent multipath declining, and other advantages, it has happened found expected important for localization in IOTs. It performs well in a Wi-Fi sensor network (WSN) and has been looked into as a attainable option for household localization. We present the age and gathering of UWB signal first and afterward we test the confinement calculation for IoT uses utilizing UWB detached innovation.

Author(s) Details:

B. Venkata Krishnaveni,
ECE Department, CMR Institute of Technology, Hyderabad, Telangana, India.

A. Venkatalakshmi,
ECE Department, CMR Institute of Technology, Hyderabad, Telangana, India.

B. Ravi Kumar,
ECE Department, CMR Institute of Technology, Hyderabad, Telangana, India.

Please see the link here: https://stm.bookpi.org/CPSTR-V2/article/view/12859

Massive Data Analysis, IoT Perspective | Book Publisher International

Massive data is a new force driving global economic and social transformations. The global data collection is reaching a tipping point for substantial technical advances that can bring about new approaches to decision-making, the management of our health, cities, finances, and education. While data complexities are increasing, including data's volume, diversity, velocity, and veracity, large data analytics technologies have the greatest impact on our capacity to discover the 'value' in the data. Massive data analytics poses a grand challenge on the design of highly scalable algorithms and systems to integrate the data and uncover large hidden values from datasets that are diverse, complex, and of a massive scale. Potential innovations include new algorithms, techniques, systems, and applications in massive data analytics that efficiently and effectively uncover useful and concealed knowledge from massive data. This book provides the fundamental concept and tools required to handle the massive data along with a use case.

Author(s) Details:

Priyanka Tripathi,
Department of Computer Applications, National Institute of Technology, Raipur, India.

Vidyapati Jha,
Department of Computer Applications, National Institute of Technology, Raipur, India.

Please see the link here: https://stm.bookpi.org/MDAIP/article/view/11808

EcoFlex DC-DC Converter Optimization Using a Stochastic-Heap Hybrid Optimizer and IoT Technology | Chapter 12 | Research and Developments in Engineering Research Vol. 7

The climbing need for energy-efficient capacity electronics in Internet of Things (IoT)-authorized devices requires the invention of advanced optimization methods. The EcoFlex DC-DC converter, a new energy-effective solution, is received in this chapter, in addition to a proposal for its growth using an IoT-integrated theory of probability-heap hybrid optimizer (SHHO). The main aims are to produce an eco-friendly DC-DC preacher, an IoT-based switching control bettering, and a low-capacity converter. The widespread use of Internet of Things (IoT) designs in recent years has raised demand for power electronics schemes that meet networked intelligent maneuvers' varied and changing strength requirements. Innovative power administration systems that can affect a balance between energy frugality, agility, and environmental knowledge are urgently needed as IoT uses continue to evolve. A prospective solution to these questions is the EcoFlex DC-DC converter, which this stage covers. It is meant to maximize strength use while allowing for the vacillating load requirements of IoT-enabled supplies. The Stochastic-Heap Hybrid Optimizer (SHHO), which combines the benefits of guessed exploration accompanying heap-based exploitation, is used to reach this. Improving the EcoFlex DC-DC converter's effectiveness is the basic goal of this work. The SHHO optimizes the EcoFlex preacher's settings to obtain high energy effectiveness, which lowers total energy payments and promotes tenable operation. The chapter's second aim is to use IoT technologies to reinforce EcoFlex converter control.In this book chapter, investigators and engineers may test the EcoFlex converter's potential as a high-efficiency power management alternative for the developing IoT system countryside. These results and conclusions prepare the way for further investigation into optimizing power camcorders and support the growth of environmentally friendly and strength-efficient IoT ploys.

Author(s) Details:

Praveen Mande,
Department of EECE, GITAM University, Vishakhapatnam, India.

Budidi Udaya Kumar,
Department of EECE, GITAM University, Vishakhapatnam, India.

S. V. Bharath Kumar Reddy,
Department of EECE, GITAM University, Vishakhapatnam, India.

Sreenivasulu Ummadisetty,
Department of EECE, GITAM University, Vishakhapatnam, India.

I. E. S. Naidu,
Department of EECE, GITAM University, Vishakhapatnam, India.

Please see the link here: https://stm.bookpi.org/RADER-V7/article/view/11712

Stochastic-Heap Hybrid Optimizer (SHHO) and Control Strategies for AC to DC Converters in IoT Applications | Chapter 11 | Research and Developments in Engineering Research Vol. 7

The rebellious effects of the Internet of Things (IoT) on tool interaction and communication have happened in significant development in the adoption of IoT-based requests. Effective power source exercise is crucial in IoT uses, especially in settings accompanying constrained strength resources. AC to DC converters plays a crucial part in the present position by converting interspersing current into direct current. This conversion procedure helps to increase strength efficiency and create it easier to include energy from undepletable source sources. The Stochastic-Heap Hybrid Optimizer (SHHO) is a finish that may be used to help the energy efficiency and control plans of AC to DC converters in Internet of Things (IoT) applications. As submitted, the SHHO method combines guessed search methods accompanying a heap-based addition strategy to efficiently investigate the solution room. SHHO successfully overcomes the local optima question by using the capacities of randomization and prioritization, leading to revised convergence and greater acting. This chapter still comprehensively resolves several AC-to-DC converter control algorithms that concede possibility be used in IoT plans. The solutions include containing, procedures like Proportional-Integral-Derivative (PID) control, Maximum Power Point Tracking (MPPT), and Pulse Width Modulation (PWM). These control methods' examination and contrasting shed light on their distinct benefits and restraints in diverse IoT backgrounds. Additionally, this chapter explores the troubles encountered when SHHO (Solar Hybrid Home Optimisation) is linked with IoT-located AC-to-DC converters. Real-time operation, fittings limits, and communication limits are all part of these difficulties. The authors further discuss useful implementation issues and focal point prospective applications place SHHO might considerably increase performance and energy adeptness. To verify the productiveness of the suggested SHHO and control means, extensive simulations and experimental tests are completed activity in typical IoT positions. According to the findings, SHHO performs better than usual optimization systems in terms of influence, dependability, and flexibility. The Stochastic-Heap Hybrid Optimizer and control arrangements for AC to DC converters are thoroughly checked in this book chapter for use in Internet of Things uses. The approaches and conclusions argued in this information improve the development of strength-efficient IoT wholes. This development sets the stage for the next smart and tenable IoT deployments.

Author(s) Details:

I. E. S. Naidu,
Department of EECE, GITAM University, Vishakhapatnam, India.

Praveen Mande,
Department of EECE, GITAM University, Vishakhapatnam, India.

Budidi Udaya Kumar ,
Department of EECE, GITAM University, Vishakhapatnam, India.

S. V. Bharath Kumar Reddy,
Department of EECE, GITAM University, Vishakhapatnam, India.

Sreenivasulu Ummadisetty,
Department of EECE, GITAM University, Vishakhapatnam, India.

Please see the link here: https://stm.bookpi.org/RADER-V7/article/view/11711

Role of Artificial Intelligence and Machine Learning for Enabling IoT-Enabled Healthcare Systems | Chapter 4 | Research and Applications Towards Mathematics and Computer Science Vol. 2

 The Internet of Things (IoT) and machine intelligence (AI) technologies are a organic match for future expansion. IoT uses the computer network to link everything in the sphere. IoT devices have infinite information in chips and sensors because there are many connected devices, which resources there is plenty data that maybe used to empower individuals completely facets of their history. The significant amount of dossier created by IoT devices is excessive for even humans and calculating algorithms to analyse and analyse. Algorithms for machine learning and artificial intelligence so aid in ruling them. The working answer to ruling the numerous linked IoT elements is provided by AI. Learning proficiencies and limitless data conversion that are produced by IoT devices are the important concern. The businesses are engaging machine learning (ML), a potent arm of artificial intelligence (AI), to resolve this problem. The smart wholes give an accurate forecast for asking ML to IoT data. IoT AI requests help businesses decrease unscheduled downtime, create new aids and products, run more capably, and manage risk better. In healthcare, smart homes, independent cars, farming, and marketing, this alliance is mostly employed. This survey study addresses healthcare uses based on machine intelligence (AI) and the internet of belongings (IoT) in these numerous applications. Additionally, it presents a review of various IoT AI algorithms for early illness prophecy in the medical field.

Author(s) Details:

Aanchal Tehlan,
Maharaja Surajmal Institute, IP University, New Delhi, India.

Ankita Moharana,
Department of Pharmaceutics, School of Pharmacy, ARKA JAIN University, Jamshedpur, Jharkhand, India.

Gowri Sankar Chintapalli,
Department of Pharmaceutics, School of Pharmacy, ARKA JAIN University, Jamshedpur, Jharkhand, India.

P. Arockia Mary,
Department of Information Technology, V.S.B. Engineering College, Karur, Tamilnadu, India.

Snigdha Rani Behera,
Department of Pharmaceutical Analysis, School of Pharmacy, ARKA JAIN University, Jamshedpur, Jharkhand, India.

Please see the link here: https://stm.bookpi.org/RATMCS-V2/article/view/11107