No abstract

The proposed approach uses blockchain-based technology to strengthen the data security of wireless sensor networks (WSNs). This paper integrates blockchain-based technology with data transfer to establish an extremely secure WSNs structure. The present wireless network is built on the architecture of the Internet of Things (IoT) and employs a blockchain-based method to make the reliability of data transmission strong. In this proposed research, many small-area wireless sensor networks establish the entire WSNs structure, and every small-area wireless sensor network has a primary data collection node called a "mobile database." The "mobile database" node of this study uses embedded microcontrollers with an operating system, such as Raspberry Pi and Arduino Yun. This block contains the sensor data collected by itself and the hash value of the previous block. Then the hash value of its own block, which is also part of the hash calculation of the next block, was calculated through the mining calculation program. Any block in the proposed method includes the encrypted hash-value of the previous block, the current timestamp, and the transaction data. In our research content, the transaction data is represented as wireless network sensing data. Basically, the system employs the hash function for calculation using the Merkeltree algorithm. Such programming makes the block with blockchain-based technology difficult to tamper with content. This study approach revises the blockchain-based transaction ledger to become a sensor data record. Therefore, the proposed system gathers and analyzes sensor data for more reliability in the wireless sensing network structure. Furthermore, the innovative system with blockchain-based technology can treat a private cloud-end. This paper also carries on to visualize the uploaded sensing data by the sensors and draws corresponding charts based on big data analysis. The wireless network architecture proposed in this paper is built on embedded devices, making it easy for the system to build a web server. Using Python or JavaScript programming language in the web environment is relatively more convenient for data visualization and data analysis.Finally, this study uses traditional methods and innovative methods to compare data transmission. When the system uses innovative methods with blockchain-based technology, it is almost impossible for any operator to tamper with the data transmitted by the sensor.

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.

The foremost purpose of this study is to use wireless sensor network (WSN) technology to build an intelligent fish-vegetable coexistence system. As a traditional fish-vegetable coexistence system lacks intelligent diagnoses, personnel and the original materials are difficult to control, and efficiency is low. We expect to remotely monitor the environmental values of the fishvegetable coexistence system at any time through Internet of Things technology and to control the feeding time and the brightness of LED lamps. The key concept of this system is to "let the fishes be farmers", meaning that when the system is balanced, the nutrient supply and water purification can form a good circulation system as long as fish feed is provided and the evaporated moisture is supplemented in a timely manner. The main control board of the system is an Arduino Mega 2560, and the ZigBee communication protocol is used as a wireless transmission tool, which is combined with a temperature humidity sensor and an illuminance sensor. Thus, the performance of the traditional temperature humidity sensor is improved, and the fish yield is increased. Real-time monitoring can minimize the loss of fish. This expert system increases the success rate of culturing and planting, and the overall system efficiency is increased. Our team creates a human-computer interaction interface using the C# programming language. This interface can be used to monitor the current sensing values and store the data in an Excel data sheet, thus allowing users to query and analyze previously detected data. Users can monitor the system operation status and control the load through the designed human-machine interface to achieve smart network remote monitoring.

With the development and progress of technology, people’s requirements for living quality are increasingly higher. This study builds an indoor thermal comfort environmental monitoring system through the Internet of Things (IoT) architecture to explore the thermal comfort of people in indoor environments. Then, the applicable indicators are selected from a series of thermal comfort pointers, and the controllable indoor environmental parameters are analyzed and simulated on MATLAB to obtain the impact on the thermal comfort indicators, which can serve as important data to set up the fuzzy rule base. Next, according to the ISO7730 comfort standard and energy saving, three ways to control thermal comfort are proposed. With Arduino UNO as the development substrate, the sensing nodes for the indoor environment are set up, and the wireless sensing network is configured with ESP8266 to transmit the sensing data to the terminal. Monitored by the C# human-machine interface, the controllable load is controlled by wireless remote mode. Finally, the data is stored in the database for follow-up experimentation and analysis. Through actual measurement experiments, the thermal comfort and energy saving effects, under comfort, general, and energy-saving modes, as proposed in this study, are verified to achieve a balance between thermal comfort and energy saving.