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IoT and Sustainability Energy Systems: Risk and Opportunity
As IoT (Internet of Things) and smart technologies have developed rapidly, many technological advancements have been made possible. The IoTs main objective is to assist in simplifying processes in a number of different felds, to improve the effciency of technologies and protocols, and ultimately to improve quality of life. Although IoT technologies can beneft the population in numerous ways, their development must be evaluated from an environmental viewpoint to ensure that global resources are used effciently and to prevent negative effects. As previously described, considerable research effort is needed to explore the advantages and disadvantages of IoT technologies. Engineering professionals, industrial experts, and academic researchers successfully interacted at the conference. Several key tracks made up the conference, including smart city, energy and environment, e-health, and engineering modeling. Specifcally, the editorial covered a number of topics including (i) IoT in sustainable energy and environmental management, (ii) smart cities enabled by IoT, (iii) ambient assisted living, and (iv) IoT technologies for transportation and low-carbon products. An important outcome of our introductory analysis has been a greater understanding of both the scientifc developments in IoT applications and the potential ecological consequences associated with increasing IoT applications. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
IOT and UAV Integrated System for Proactive Crop Disease Prediction
The productivity of agriculture is often affected by the crop diseases incurring economic loss and reduced food production. Detecting these crop diseases in the early stages is the need of the hour to mitigate the spread of the disease and manage the crop yield effectively. This paper presents a proactive crop disease prediction system by employing the technologies such as Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) to detect and mitigate the crop disease at early stages. The employed UAVs have a high resolution camera to capture the aerial images of crops and leaves. The images captured via UAVs are transferred to a computing environment dynamically for analysis purposes. The analysis is performed on the images to predict the disease of the leaf along with its intensity. After analyzing and predicting the leaf disease and its intensity, the pesticide information is passed to the IoT sensors which are fixed in the fields to spray the recommended pesticide. The system analyzes the captured images by leveraging the machine learning algorithms in the realtime to identify different diseases and predict the spread of the disease. The proposed proactive approach helps the farmers to take preventive actions to identify the crop disease at the early stage and mitigate them in a timely manner to produce a better crop yield. Moreover, the proposed method provides a cost-effective solution for disease prediction and is easily accessible to farmers to enhance crop productivity. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine
Presently, wearables act as a vital part of healthcare sector and they are able to offer exclusive perceptions about the person's health conditions. In contrast to traditional diagnosis in a hospital environment, wearables can give unrestricted access to real-time physiological data. COVID-19 epidemic is increasing at a faster rate with limited test kits. Hence, it becomes essential to develop a novel COVID-19 diagnostic model. Numerous studies were based on the utilization of artificial intelligence techniques on radiological images to precisely identify the disease. This chapter presents an efficient fusion-based feature extraction with multikernel extreme learning machine (FFE-MKELM) for COVID-19 diagnosis using internet of things (IoT) and wearables. Primarily, the wearables and IoT are used to capture the radiological images of the patient. The presented FFE-MKELM model incorporates Gaussian filtering based preprocessing for removing the noise that exists in the radiological image. Besides, directional local extreme patterns with deep features based on Inception v4 model are applied for the FFE process. In addition, MKELM model is utilized as a classification model to determine the appropriate class label of the input radiological images. Moreover, monarch butterfly optimization algorithm is applied to fine tune the parameters involved in the MKELM model. Experimental validation of the FFE-MKELM model is performed against benchmark dataset and the outcomes are inspected under different measures. The resultant simulation outcome ensured the betterment of the FFE-MKELM method by demonstrating an increased sensitivity of 97.34%, specificity of 97.26%, accuracy of 97.14%, and F-measure of 97.01%. 2022 Elsevier Inc. All rights reserved. -
IOT based air quality sensor device /
Patent Number: 358781-001, Applicant: Dr.Sarwesh P. -
IOT based application for monitoring electricity power consumption in home appliances
Internet of Things is one of the emerging techniques that help in bridging the gap between the physical and cyber world. In the Internet of Things, the different smart objects connected, communicate with each other, data is gathered from the smart objects and based on the need of the users, and the data gathered are queried and sent back to the user. IoT helps in monitoring electrical and physical parameters. Electricity consumption from electronic devices is one among such parameters that need to be monitored. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper proposes a Wi-Fi enabled simple low cost electricity monitoring device that can monitor the electricity consumption on home appliances which helps to analyses the consumption of electricity on a daily and weekly basis. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
IOT based application to detect fall with a measured force
Fall of patients and aged individuals may end up deadly if unnoticed in time. A fall detection framework has been developed which sends caution notification to the concerned individuals or to the specialist, at the time of occurrence. To limit the consequences of associated wounds/damage caused by the fall, such a device has been developed. The model in this study, detects the fall and measures the force of the fall without using the force sensor and the direction of the fall. In this study, the body posture is obtained from change of increasing speed in three axes, which is measured with a triaxial accelerometer (ADXL335). The sensor is set on the lumbar area to interpret the tilt point. The value obtained from the sensor is compared with the threshold given to diminish the false cautions and furthermore provides the force by which the individual has fallen and the direction in which the person has fallen. The threshold value is computed by the execution of various trials on subjects in different directions of fall. The sensor data is collected on the fall is computed and analyzed in the Audrino microcontroller. The location of fall is detected by GPS beneficiary, which is customized to trace the subject persistently. On detecting the fall, the gadget sends an instant message through GSM module to the emergency contact. The developed model is tested on 7 volunteers who replicated falls in different direction with varying forces. Out of 28 trials, 80% of exactness is accomplished with zero false cautions for dayto-day activities like sitting, lying down on bed and grabbing objects. IAEME Publication. -
IoT Based Bus Identification and Distance Notifier for the Visually Impaired
Public transport is a major obstacle for the visually impaired, and it tends to limit their independence and mobility. To overcome this problem, the current project presents an IoT-based bus identification and distance notification system that is meant to offer real-time support and improve the traveling experience of the visually impaired commuters. The system uses a Raspberry Pi controller in combination with an RFID reader and several RFID cards, each one of which is designated for a particular bus, to detect oncoming vehicles. A GPS unit monitors the position of the bus at all times, so it is possible to calculate exact distances to any of the stops. For additional convenience, the system includes three push-button switches programmed to three predetermined bus stops. Users may pick their destination stop, and the system will offer auditory feedback in terms of distance to the selected destination. Feedback is offered by an earphone, providing hands-free use and receiving instructions without visual interaction. The integration of RFID-based bus identification, GPS location, and voice guidance provides smooth real-time information, less reliant on outside help. The system increases mobility confidence through accurate, timely, and convenient information, enabling blind travelers to make use of public transport independently. Through the combination of IoT technology and assistive technologies, the project enables enhanced accessibility and inclusion in urban mobility systems. 2025 IEEE. -
IoT based car accident detection and notification algorithm for general road accidents
With an increase in population, there is an increase in the number of accidents that happen every minute. These road accidents are unpredictable. There are situations where most of the accidents could not be reported properly to nearby ambulances on time. In most of the cases, there is the unavailability of emergency services which lack in providing the first aid and timely service which can lead to loss of life by some minutes. Hence, there is a need to develop a system that caters to all these problems and can effectively function to overcome the delay time caused by the medical vehicles. The purpose of this paper is to introduce a framework using IoT, which helps in detecting car accidents and notifying them immediately. This can be achieved by integrating smart sensors with a microcontroller within the car that can trigger at the time of an accident. The other modules like GPS and GSM are integrated with the system to obtain the location coordinates of the accidents and sending it to registered numbers and nearby ambulance to notify them about the accident to obtain immediate help at the location. 2019 Insitute of Advanced Engineeering and Science. All rights reserved. -
IoT based continuous monitoring of cardiac patients using Raspberry Pi
In the recent development the Internet of Things (IoT) brings all electronics objects in to a single domain and it is easy to access everything through internet. The applications of IoT are Smart agriculture, Smart Home, Smart City, Smart health monitoring system etc. The automation of health care is one of the application which monitors the patient health status using IoT to make medical equipments more efficient by monitoring the patient's health, in which identifies the body conditions and reduces the human error. A health care monitoring system is used to monitor patient's body parameters for the particular disese and obtain the various values about it. The heart rate monitor is one of the in system using IoT to recognize the cardic patients condition and monitor the status in emergency situations. It monitors the heart rate of the patient with long term cardiovascular disease. Here the Arduino based microcontroller is used to communicate to the sensors such as pulse sensor and ECG Sensor. The system can analyze the signal, extract features from it, detect the normal or abnormal conditions with the help of Raspberry Pi and the results of the ECG signals is sent to the web server. It ensures the signal transmission of heart rate signal to the database through IoT. This also suggests doctors to care the patient follow-up their patient using the patient's data stored in the database. Thus IoT brings one of the solution for cardiac patient monitoring and also reduces the complexity between patient outcome and technology. 2018 Author(s). -
IoT Based Enhanced Safety Monitoring System for Underground Coal Mines Using LoRa Technology
Extracting coal from Underground mine is a hazardous and tough job that needs continuous monitoring of environmental conditions to protect workers health and safety. Though some research works have explored wireless monitoring devices for underground mining, such as ZigBee and Wi-Fi technologies, they come with inherent restraints for instance restricted coverage, susceptibility to interference, reliability issues, security concerns, and high-power consumption. An Enhanced Safety Monitoring System for coal extraction from Underground Mines, employing LoRa communication technology for the effectual transmission of collected data to overcome existing challenges is discussed in this paper. The proposed system consists of two subsystems, one for monitoring the status of miners and another for comprehensive monitoring. LoRaWAN (Long Range Wide Area Network) is a multipoint protocol and this media access control (MAC) enables low-power devices to establish communication with Internet of Things (IoT) applications over extended wireless connections for long-range networks. LoRaWAN operates on lower radio frequencies, thereby providing a longer range of communication. This technology is known for its efficiency in optimizing LPWAN, offering extended range, extended battery life, robustness, and cost-effectiveness, making it highly suitable for industrial mining applications. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
IOT based Green House monitoring system
With industrialization and continuously evolving climatic conditions, the urge to practice agriculture with the fusion of technology has become a necessity. In the era of Internet of Things where all eyes are witnessing the evolution of machine to machine interaction, there is also a lack of clarity in considering the type of protocol to be used in building a particular system like Green House. A green house is a regulated environment for agriculture where critical parameters like temperature, light, humidity, ph level of soil can be monitored with the help of sensor systems using Internet of Things protocols. Message Queue Telemetry Transfer protocol was chosen over Constrained Application Protocol and Extensible Messaging and Presence Protocol in the experiment conducted in terms of its light weight transmission, resource consumption and effectively providing the different quality of services to detect the temperature and humidity as well as the gas leaks encountered in a greenhouse environment. 2018 Tinu Anand Singh and J. Chandra. -
IoT based heart monitoring and alerting system with cloud computing and managing the traffic for an ambulance in India
Global Burden of Disease Report, released in Sept 2017, shows that Cardiovascular Diseases caused 1.7 million deaths (17.8%) in 2016 and it is the leading cause of deaths in India [1]. According to the Indian Heart Association, 25% of all heart attacks happen under the age of 40. In most cases, the initial heart attacks are often ignored. Even post-diagnosis, as per government data [2], 50% of heart attack cases reach the hospital in more than 400 minutes against the ideal window time of 180 minutes; post which damage is irreversible. The delay is often attributed to delay in reaching a hospital or receiving primary aid. In India, traffic conditions also add to the grimace of the situation. Although the government is taking various measures; a holistic solution is required to minimize the delay at each of the steps like accessing the patient situation, contacting the Medical aid or making available the nearest aid possible. In this paper, we aim at providing the holistic solution using the Internet of Things technology (IOT) along with data analytics. IoT enables real-time capturing and computation of medical data from smart sensors built-in wearable devices. The amalgamation of Internet-based services with Medical Things (Smart sensors) enhance the chances of survival of patients. The proposed system analyses the inputs collected from the sensors fit with the patients prone to cardiovascular diseases to ascertain the emergency situation. In addition, to these data, the system also considers age, maximum and minimum heart rate. Based on computational results received from the input parameters, the system triggers the alert to emergency contacts such as the close relatives of the patient, doctors, the hospitals and nearby ambulance. The proposed system combines with the optimized navigation platform to guide the medical assistance to find the fastest route. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
IoT based hybrid patient health monitoring system
According to the data released by the World Health Organization (WHO). Cardiovascular diseases (CVDs) are still the leading thread worldwide. Every year around 17.9 million fatalities worldwide are attributed to CVDs, making up 31% of overall deceases. Heart attacks and strokes are the main causes account for most of these deaths, and a large fraction happen so early in the age group of under 70. Check-ups are essential to monitor the healthcondition of the elderly people, which generates a considerable challenge to the existing medical field. Subsequently,It's becoming more crucial to diagnose diseases quickly and accurately with an affordable cost. The World's population growth need for a smart and affordable healthcare solutions to reduce the medical costs. Thus, the development of an effective health monitoring system that can quickly identify irregularities in health and provide precise diagnoses based on gathered data is imperative. New developments in cloud computing and mobile technologies have led to the development of a number of cloud-based healthcare products and services. These cloud systems allow for the automatic collection and transmission of medical data to providers from any place, allowing for the network-based delivery of patient feedback. This project's goal is to use the ThingSpeak IoT platform to create and implement an Internet of Things-based patient health monitoring system in order to meet these goals. 2026 Author(s). -
IOT based intelligent traffic management system /
Patent Number: 202131062286, Applicant: Bikas Mondal.
As the population grows and there are more cars on the roads, a large number of people may visit a site. It may be difficult for those who work there to keep track of everyone who comes in. Cloud-based interconnection between vehicles will benefit traffic cops by allowing them to monitor traffic and flow patterns without having to get out and do anything. Customers with valid driver's licences can only use a vehicle with an automatic ignition that is solely based on biometrics. -
IOT based intelligent traffic management system /
Patent Number: 202131062286, Applicant: Bikas Mondal.
As the population grows and there are more cars on the roads, a large number of people may visit a site. It may be difficult for those who work there to keep track of everyone who comes in. Cloud-based interconnection between vehicles will benefit traffic cops by allowing them to monitor traffic and flow patterns without having to get out and do anything. Customers with valid driver's licences can only use a vehicle with an automatic ignition that is solely based on biometrics. -
IOT based no-parking notifier system
Traffic congestion due to vehicles parked in No-parking zones has become a serious problem in major cities of India. Due to traffic congestion environment, economy and overall quality of life is affected. Hence it is high time to effectively manage the traffic congestion problem. With increase in number of vehicles, discipline in road regulation or traffic system becomes mandatory. The existing traffic system is very accurate but not efficient enough to monitor all the vehicles on the road. With the advent of new technology this problem can be tackled by using Wi-Fi enabled micro-controllers, RFID and cloud systems to monitor every vehicle on the road all the time. This becomes easy for the government in regulating its traffic rules with high efficiency without affecting the smoothness of the traffic. 2018 IEEE. -
IOT based plant disease detection using support vector machine algorithm /
Patent Number: 202021050705, Applicant: Dr. Chaitanya Singh.
Internet of Things integrated with image processing paves new ways for monitoring plant health and actuating response based on recent development of technologies. Early detection of plant diseases and its classification utilizes image processing along with analysis of environmental data which will help farmers to maximize their yield by producing healthy plants as plant diseases are eradicated at the initial stage. -
IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting. 2023 The Authors -
Iot based real time potholes detection system using image processing techniques
Accidents owing to potholes has become an alarming problem in todays life. The first step to solve this problem requires, designing a device embedded on the vehicle which can continuously scan the road surface for identifying potholes, alerting the driver in time and enable the driver to avoid the pothole. The second step is to introduce a technique to enable the device to locate the position of the pothole via GPS (Global Positioning System). The GPS data can be uploaded via a GPRS (General Packet Radio Service) module or Bluetooth module onto a data base which is stored locally. This database can then be transferred to the cloud using WiFi or 4G technology by connecting the system. The third aspect is to link the database to a network system incorporating mapping software such as Google Maps or Open-Street Map. The data in the system can be made available to the general public as well as municipalities and road maintenance agencies. Awareness of the location of potholes will help drivers to avoid those roads and being more careful while driving on the same roads. This paper focuses on the pothole detection task based on image processing algorithms and the data captured from ultrasonic sensor placed on the vehicle. The later steps were implemented through Bluetooth interface available in smartphones. IJSTR 2020. -
IoT Based Risk Monitoring System
The Internet of things (IoT) aims at connecting different objects, things using internet. The IoT is expanding rapidly and this motivates to apply for the food preservation domain such as preserve the standard of the veggies and fruits. In this paper we have worked on a cold storage system to analyze the environmental conditions under which the food item is being stored. The proposed system senses the temperature, moisture, gas parameters of surrounding environment as these parameters affect nutritional values of food items. An Arduino-based system is created and put into operation; it serves as both a central hub and a network layer for the refrigerated holding tank. It is also linked to the cloud, where an open-source application server supports digital storage functions. By establishing a connection to the database (DB) via its IP address, the measured variables are delivered to the base station (BS) from the cloud and stored there. Then, a cooperative sensing model that uses many observed information as input and one merged informational item or action to be performed as output is tried. As a result, numerous inputs, such as temperature and humidity, were combined and averaged to provide a tightly integrated result. Last, the system integrated an android mobile application which is used to facilitate user interaction and connect through IoT based system that is station or gateway and the internet. GPS is Used to track the remote cold storage and transport container live locations. 2022 IEEE.