Smart Follower Sensing Shopping Cart using Centralized Billing System

In the age of technological advancements, automation is essential to improve and streamline processes. Since last few decades,technology has transformed the landscape of industries and lifestyle .The proposed system suggests implementing a smart cart using a touchscreen liquid crystal display (LCD) which will show the product details using Radio Frequency Identification (RFID).The LCD displays an overview of the entire supermarket showing all the different sections available helping the customer to find products. The system has a centralized billing system because of the customer need not wait in long queues for the final billing process which will eventually save his/her time. Machine automation has starting replacing human effort .With a view to accomplish this ,the customer does not have to move the cart ,instead the cart will follow the customer. A RF receiver is fixed inside the cart and the transmitter is given handed over to the customer . The information of the product added in the cart by the customer is stored in Electrically Erasable Programming Read Only Memory (EEPROM). Once the customer is done with shopping and clicks the finish button all the information will be transferred to the administrative system using Zigbee

Edge computing in multi-scope service-oriented mobile healthcare systems

IoT based e-Health solutions is an upcoming trend which will revolutionize the healthcare in the near future. IoT has evolved from micro-electro-mechanical systems (MEMS), wireless technologies and Internet which together offer connectivity of systems, microelectronic devices, and medical services and allow data processing at the edge. That at the same time allows to save computational resources and avoid unnecessary point of failure, such as centralized synchronization point. Monitoring of patients’ vital signs parameters (measured at home) is achieved by using modern Internet of Things technology which provides networkable connections between portable diagnostic sensors, their cell phones, cloud data storage with patients’ Personal Health Records and professional health providers. This paper explores possibilities of using fog computing approach to shift data processing and computations from cloud to the edge and to build a multi-scope infrastructure for mHealth and citizen-observation system, based on SOA approach

A Systematic Review of IoT Communication Strategies for an Efficient Smart Environment

The massive increase in actuators, industrial devices, health-care devices, and sensors, have led to the implementation of the Internet of Things (IoT), fast and flexible information technology communication between the devices. As such, responding to the needs in speedily way, and matching the smart services with modified requirements, IoT communications have facilitated the interconnections of things between applications, users, and smart devices. In order to gain extra advantage of the numerous services of the Internet. In this paper, the authors first, provided a comprehensive analysis on the IoT communication strategies and applications for smart devices based on a Systematic Literature Review (SLR). Then, the communication strategies and applications are categorized into four main topics including device to device, device to cloud, device to gateway and device to application scenarios. Furthermore, a technical taxonomy is presented to classify the existing papers according to search-based methodology in the scientific databases. The technical taxonomy presents five categories for IoT communication applications including monitoring-based communications, routing-based communications, health-based communications, Intrusion-based communications, and resource-based communications. The evaluation factors and infrastructure attributes are discussed based on some technical questions. Finally, some new challenges and forthcoming issues of future IoT communications are presented

Unveiling the core of IoT: comprehensive review on data security challenges and mitigation strategies

The Internet of Things (IoT) is a collection of devices such as sensors for collecting data, actuators that perform mechanical actions on the sensor's collected data, and gateways used as an interface for effective communication with the external world. The IoT has been successfully applied to various fields, from small households to large industries. The IoT environment consists of heterogeneous networks and billions of devices increasing daily, making the system more complex and this need for privacy and security of IoT devices become a major concern. The critical components of IoT are device identification, a large number of sensors, hardware operating systems, and IoT semantics and services. The layers of a core IoT application are presented in this paper with the protocols used in each layer. The security challenges at various IoT layers are unveiled in this review paper along with the existing mitigation strategies such as machine learning, deep learning, lightweight encryption techniques, and Intrusion Detection Systems (IDS) to overcome these security challenges and future scope. It has been concluded after doing an intensive review that Spoofing and Distributed Denial of Service (DDoS) attacks are two of the most common attacks in IoT applications. While spoofing tricks systems by impersonating devices, DDoS attacks flood IoT systems with traffic. IoT security is also compromised by other attacks, such as botnet attacks, man-in-middle attacks etc. which call for strong defenses including IDS framework, deep neural networks, and multifactor authentication system

IoT-HASS: A Framework For Protecting Smart Home Environment

While many solutions have been proposed for smart home security, the problem that no single solution fully protects the smart home environment still exists. In this research we propose a security framework to protect the smart home environment. The proposed framework includes three engines that complement each other to protect the smart home IoT devices. The first engine is an IDS/IPS module that monitors all traffic in the home network and then detects, alerts users, and/or blocks packets using anomaly-based detection. The second engine works as a device management module that scans and verifies IoT devices in the home network, allowing the user to flag any suspect device. The third engine works as a privacy monitoring module that monitors and detects information transmitted in plaintext and alerts the user if such information is detected. We call the proposed system IoT-Home Advanced Security System or IoT-HASS for short. IoT-HASS was developed using Python 3 and can be implemented in two modes of operation. The in-line mode allows the IoT-HASS to be installed in-line with the traffic inside a Raspberry Pi or a Router. In the in-line mode IoT-HASS acts as an IPS that can detect and block threats as well as alert the user. The second mode is the passive mode where IoT-HASS in not installed in-line with the traffic and can act as an IDS that passively monitors the traffic, detecting threats and alerting the user, but not blocking the attack. IoT-HASS was evaluated via four testing scenarios. It demonstrated superior performance in all testing scenarios in detecting attacks such as DDoS attacks, Brute Force Attacks, and Cross Site Scripting (XSS) Attacks. In each of the four test scenarios, we also tested the device management functionality, which we found to successfully scan and display IoT devices for the homeowner. The extensive evaluating and testing of IoT-HASS showed that IoT-HASS can successfully run in a small device such as a Raspberry Pi, and thus, it will most likely run in an embedded device as an IoT device. Our future research will concentrate on strengthening the current features of IoT-HASS to include additional functionalities