Technology is continually evolving, and Blockchain development in recent years has shown tremendous adaptability. Blockchain’s emphasis lies mainly in the finance sector, but some latent fields such as healthcare still grow and transform the future. In this paper, we introduced a smart contract-based framework for Blockchain-based healthcare system. According to our hypotheses, the proposed framework in the healthcare system will be changed by leveraging the principles and technologies of a public ledger, which will change the healthcare industry’s vision based on Blockchain. Health records, laboratory evaluation results, doctoral perceptions, and precise information about health care can be decentralized in the form of blocks in the form of transactions. These blocks can be linked in Blockchain as distributed ledgers according to the series of events. It can eliminate a highly complex process and manual intervention. Through adding an Identity Manager, fully open and secure applications can be based on Blockchain technologies. Based on the expected outcomes, we are optimistic that the proposed Blockchain-based framework will be helpful in the healthcare context; to evaluate the maturity level of our proposed framework we map the framework on Ethereum-based application and evaluated in the hospital setting, for the evaluation of the proposed framework. At the initial stage, we are confident that the proposed framework will be helpful in the hospital environment and contribute to enhancing the performance of the healthcare environment.

A remix IDE: smart contract-based framework for the healthcare sector by using Blockchain technology

This article aims at saving the wasted water in the process of irrigation using the Internet of Things (IoT) based on a set of sensors and Multi-Layer Perceptron (MLP) neural network. The developed system handles the sensor data using the Arduino board to control the water pump automatically. The sensors measure the environmental factors; namely temperature, humidity, and soil moisture to estimate the required time for the operation of water irrigation. The water pump control system consists of software and hardware tools such as Arduino Remote XY interface and electronic sensors in the framework of IoT technology. The machine learning algorithm such as the MLP neural network plays an important role to support the decision of automatic control of IoT-based irrigation system, managing the water consumption effectively.

IoT and Neural Network-Based Water Pumping Control System For Smart Irrigation.

The Health Effects Institute (HEI) reported recently that the deaths from the negative health effects of the air pollution in the Middle East Region is about 500,000 people. Therefore, this paper presents a new design and development of portable system; called GASDUINO that allows the user to measure the quality of air using the Internet of Things (IoT). The main components of developed GASDUINO system are the Arduino microcontroller board, Gas sensor (MQ-135), Android user interface (UI) connected with all things via Remote XY Arduino cloud. The developed system can alarm the users about the dangerous levels of the air quality index (AQI) or the particle per million (PPM) levels in the range of 0 to above 200 PPM. The developed GASDUINO system is considered as an essential environmental module in the development and sustainability of future smart cities.

GASDUINO-Wireless Air Quality Monitoring System Using Internet of Things.

In the interior of image texture analysis methods, many types, behavior, strategies, modeling, and characteristics are employed. Several surveys and reviews are illustrated in the literature regarding image texture and feature extraction using an agent and multi-agent-based systems. Nevertheless, few determinations are made in the context of the image texture feature extraction. Hence, the overall aim of this paper is to provide an overview of the image texture and feature extraction concepts depicted in the literature for characterizing regions in images by exploring the role and strategies of the agent and multi-agent systems (MAS). This paper tackles two behavior types, reactive agent (RA) and goal-directed agent (GDA), in terms of the natural surroundings of agent and multi-agent communications. In terms of MAS modeling, this paper tackles three types, including facilitator agent architecture (FAA), mediator agent architecture (MAA), an autonomous agent architecture (AAA). While for the MAS characteristics, five types are presented: interaction, coordination, cooperation, collaboration, and collectiveness. Finally, a discussion for agent and multi-agent-based feature extraction in image analysis is presented by comparing the strategies and the frequent use of the strategies in the literature. Based on this review, most of the feature extraction multi-agent-based systems rely on either coordinating or emergent-based strategies, while feature selection agent-based systems rely on collaborative strategies. However, there are several aspects that we can consider to be classified as agent-based strategies. This review develops a classification scheme for systems used in specific tasks of feature extraction.

Exploring the Roles of Agents and Multi-Agent in Image Feature Extraction

This paper introduced a highly reliable smart irrigation system with the Internet of objects or Things (IoT) Technique and neural network architecture. Smart systems using artificial neural networks (ANN) integrated with real-time hardware applications are becoming very popular in the area of IoT. This paper aims to save the waste of water for the irrigation process by utilizing an IoT and using an artificial neural network with different sensors such as FC-28 soil sensor and DHT11 sensor for measuring humidity and temperature parameters. The designed system uses two microcontrollers (Arduino and Node MCU ESP 8266) to automatically control the water pump state to be ON/OFF and control the flow of water for irrigation based on different input parameters. Input sensors measure environmental parameters such as soil moisture, air temperature, and air-humidity factors. The designed control system includes both hardware components and software programming. The ANN technique is essential for supporting the automatic control of IoT-based agriculture irrigation systems and properly regulating water use.

IoT and Artificial Neural Network-Based Water Control for Farming Irrigation System

In recent years, availability and usage of extensive systems for Electronic Healthcare Record (EHR) is increased. In medical centers such hospitals and other laboratories, more health data sets were formed during the treatment process. In order to enhance the standard of the services provided in healthcare, these records where shared and can be used by various users depends on their requirements. As a result, notable issues in the security and privacy where obtained which should be monitored and removed in order to make the use of EHR more effectively. Various researches have been done in the past literature for improving the standards of the security and privacy in E-health systems. In spite of this, it is not completely enhanced. In this paper, a comprehensive analysis is done by selecting the existing approaches and models which were proposed for the security and privacy of the E-healthcare systems. Also, a novel Intelligent-based Access Control Security Model (IBAC) based on multi agents is proposed to maintain and support the security and privacy of E-healthcare systems. This system uses agents in order to maintain security and privacy while accessing the E-health data between the users.

Application of Intelligent Multi Agent Based Systems For E-Healthcare Security

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Faizal Khan

Papers

Application of Intelligent Multi Agent Based Systems For E-Healthcare Security

Application of Intelligent Multi Agent Based Systems For E-Healthcare Security.