Today, humans pose the greatest threat to society by getting involved in robbery, assault, or homicide activities. Such circumstances threaten the people working alone at night in remote areas especially women. Any such kind of threat in real time is always associated with a sound/noise which may be used for an early detection. Numerous existing measures are available but none of them sounds efficient due to lack of accuracy, delays in exact prediction of threat. Hence a novel software-based prototype is developed to detect threats from a person’s surrounding sound/noise and automatically alert the registered contacts of victims by sending email, SMS, WhatsApp messages through their smartphones without any other hardware components. Audio signals from Kaggle dataset are visualized, analyzed using Exploratory Data Analytics (EDA) techniques. By feeding EDA outcomes into various Deep Learning models: Long short-term memory (LSTM), Convolutional Neural Networks (CNN) yields accuracy of 96.6% in classifying the audio-events.

This paper proposes a solution for ensuring the security of IoT devices in the cloud environment by protecting against distributed denial-of-service (DDoS) and false data injection attacks. The proposed solution is based on the integration of simple network management protocol (SNMP), Kullback–Leibler distance (KLD), access control rules (ACL), and moving target defense (MTD) techniques. The SNMP and KLD techniques are used to detect DDoS and false data sharing attacks, while the ACL and MTD techniques are applied to mitigate these attacks by hardening the target and reducing the attack surface. The effectiveness of the proposed framework is validated through experimental simulations on the Amazon Web Service (AWS) platform, which shows a significant reduction in attack probabilities and delays. The integration of IoT and cloud technologies is a powerful combination that can deliver customized and critical solutions to major business vendors. However, ensuring the confidentiality and security of data among IoT devices, storage, and access to the cloud is crucial to maintaining trust among internet users. This paper demonstrates the importance of implementing robust security measures to protect IoT devices in the cloud environment and highlights the potential of the proposed solution in protecting against DDoS and false data injection attacks.

In India, 47% of people are involved in the agriculture sector. A large part of the population of India depends upon the agriculture. In this work, we assemble a smart farming field screening system that helps farmers to take information about their field in the sense soil moisture, humidity and temperature of the environment. And it allows smart irrigation to the field and gives a better result for doing agriculture and provide better profit for good crop production. In our work, we can use a different type of sensors and some wireless technologies like the Internet of things (IoT) and an android application to provide a smart platform to farmers to read data from the sensors with the help of microcontroller and giving instructions in term of the graphical interface. Hence, we can use an IoT platform that gives the primary thing to access anywhere by using the internet. The Wireless sensor network consists of sensors like moisture, humidity and temperature, and Infrared sensor. Using Bluetooth and GSM module for the clustering with sensors and other microcontroller devices are connected to the solar panel or battery for the power supply. In this paper, we design an IoT platform for doing farming in an efficient way. That helps the farmers for real-time monitoring regarding their fields.