Design of low-power field wireless sensor nodes

Sensor nodes are small and low-cost portable devices that are connected wirelessly to form a wireless sensor network. Sensor nodes are typically powered by a chemical battery source that has a load-dependent finite lifetime. Most applications require wireless sensor networks to operate reliably for an extended period of time beginning with their deployment. To ensure both the longevity of a wireless sensor network via power management techniques and development of a self-powered sensor node, it is important to understand a sensor node’s operational energy consumption. It is well understood that wireless sensor network lifetime has a strong functional dependence on sensor node lifetime. This paper presents the development of a stochastic model to capture the expected energy consumption of a schedule-driven sensor node per cycle of operation by utilizing renewal theory, random stopping criteria, and Wald’s inequality. The model captures the expected energy consumed due to generic operation of a schedule-driven sensor node when an external event occurs (i.e., node level activities) and energy consumed due to carrier sense multiple access/collision avoidance medium access control protocol (i.e., retransmission attempts, channel listening, and other network level activities). The stochastic energy model is used to compute the expected lifetime and cycle lifetime of the sensor node. This paper also computes the deterministic energy bounds corresponding to the minimum and maximum energy consumption of a sensor node per cycle of operation. Analytical and numerical model validations are performed and presented.

In sensor-based activity recognition often huge amounts of data have to be acquired from multiple sensors, which need to be communicated for further processing. When using wireless sensor nodes, energy efficiency is of outstanding importance, since it directly influences the time until the battery needs to be recharged. However, communicating a huge amount of sensor data over wireless interfaces causes high energy consumption as well. Furthermore, the host controller receiving the sensor data is hindered of using its low power modes, as it needs to be woken up more frequently as well. In the paper at hand, we introduce our approach of reducing energy consumption of sensor nodes in online activity recognition scenarios by calculating the feature extraction on the sensor subsystem itself. By doing so, we can reduce the output rate of the sensor which enables the host controller to stay in its low power modes for longer periods. Additionally, this approach drastically reduces the amount of data to be transmitted over wireless interfaces, which further improves energy consumption. In our experiments, the proposed approach reduces the energy consumption of a sensor node by up to 33 %.

The efficiency of transportation system depends on many factors, such as traffic congestion, vehicle accidents and road conditions. To improve the reliability, productivity and safety of the system, many researchers propose to use a wireless sensor network (WSN) as a solution. A WSN usually consists of many tiny sensor nodes for sensing, data processing and communication. In this study, we present the development of a small-sized, low-power and lightweight wireless sensor node. It is equipped with a 3-axes accelerometer, an altimeter sensor, humidity sensor, temperature sensor, 315 MHz RF transceiver module and a typical coin-sized lithium battery (3.0 V, 220 mAh). The entire sensor node fits within a 28 × 20 × 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> volume and is only 7 grams (not including the antenna). An 8-bit MCU is included in the RF transceiver module to control sensor node operation. It collects and transmits sensors data in real time to the RF repeater with bit rate 24 kbps. During continuous operation, the sensor node consumes less than 3 mA current. Thus for a 220 mAh battery, the wireless sensor node can continue operating for more than 75 hours.

The key solution to study birds in their natural habitat is the continuous survey using wireless sensors networks (WSN). The final objective of this study is to conceive a system for monitoring threatened bird species using audio sensor nodes. The principal feature for their recognition is their sound. The main limitations encountered with this process are environmental noise and energy consumption in sensor nodes. Over the years, a variety of birdsong classification methods has been introduced, but very few have focused to find an adequate one for WSN. In this paper, a tonal region detector (TRD) using sigmoid function is proposed. This approach for noise power estimation offers flexibility, since the slope and the mean of the sigmoid function can be adapted autonomously for a better trade-off between noise overvaluation and undervaluation. Once the tonal regions in the noisy bird sound are detected, the features gammatone teager energy cepstral coefficients (GTECC) post-processed by quantile-based cepstral normalization were extracted from the above signals for classification using deep neural network classifier. Experimental results for the identification of 36 bird species from Tonga lake (northeast of Algeria) demonstrate that the proposed TRD–GTECC feature is highly effective and performs satisfactorily compared to popular front-ends considered in this study. Moreover, recognition performance, noise immunity and energy consumption are considerably improved after tonal region detection, indicating that it is a very suitable approach for the acoustic bird recognition in complex environments with wireless sensor nodes.

Proposed wireless sensor node is a highly flexible and programmable system on chip (PSoC) architecture along with integrated RF radio chip, which can be adapted to any IEEE 802.15.4 standard based protocol, working at the band of 2.4GHz.This can be accompanied by the RF antenna matched with the interface circuit for various kinds of sensors and peripherals to form a wireless sensor node.This can be very well used to form a wireless sensor network in different domains.This proposed methodology can be used for specific application for improving the WSN stability and performance.This article will mainly present the design of wireless sensor nodes based on PSoC and CyFi radio chip, including the application specific antenna and hardware design for the system on chip for the sensor node and the simple introduction of the application domain.The proposed nodes are used with a special antenna and application based protocol for communication.This design has a better power handling and performing capacity.Further, we have implemented this for the wireless sensor node as well.

Abstract. Motivated by the application of industry 4.0 and Internet of Things (IoT) technologies, the development of cyber physical systems (CPS) is gaining momentum. As CPS require multiple measurement technologies to drive the intended function, e.g., condition monitoring and in situ measurement, the integration of measurement systems into industrial processes or individual products becomes a critical activity within the development process. Development methods like the V-Model support developers with methodological guidelines, but the related methods and models do not provide sufficient information regarding the energy supply of embedded systems. If the measurement system, consisting of sensor, calculation and communication unit is integrated inside an either sealed or moveable system, e.g., in a gearbox, ensuring a reliable communication and energy supply is a challenging task. This contribution therefore focuses on the energy supply, in particular the electric power consumption of autarchic measurement systems, referred to as sensor nodes. Based on a literature review of existing physical principles determining the energy consumption of semiconductors, a simple estimation model is derived. Estimation models in the current literature mainly focus on the effects of source code or software in general without analyzing a possible impact of operation strategies, such as generic data processing logics in practical applications. The model presented in this contribution is therefore used to identify the energy consumption of sensor nodes influenced by ambient and operating conditions of sensor nodes. Strategies are examined experimentally using an exemplary sensor node, a climatic chamber and a sensor-integrated gearbox as the system to be observed. An analysis of the conducted experiments leads to a more precise model, which is evaluated regarding its significance for predicting the energy consumption and the underlying simplifications. Finally, general relations influencing the energy consumption are presented and necessary research suggested.

Recent times world has witnessed a wireless sensing networks (WSN) technology attracting for a wide range of real-world applications, mostly due to its shrinking size and cost while demonstrating improved performances and functionalities. One of the crucial factors that affect the operation of WSN is its power consumption and battery life. This paper provides an overview for designing of a low power WSN for IoT applications. Through a combination of ZigBee wireless technology, with a strong networking function, it can realize the communication between a number of Wireless Sensor Nodes. Cost-effective and low power reliable system is implemented using this protocol. Core2530 is one of the Zigbee stack available for such network solution. While considering sensor platforms and its applications, power consumption is one of the important factors to take into consideration. This paper presents the development of low power wireless sensor node for condition monitoring of railway rolling stocks.

Over the last few years, IoT devices have multiplied their number and functionality. These devices are located all over the world and batteries are their main source of energy. In this paper the usage of wireless LoRaWAN sensor node in smart Internet of Things applications was analyzed. The study focuses on the reduction of power consumption from wireless LoRaWAN sensor nodes. An analysis of the energy consumption of the various components of the architecture of the wireless sensor nodes is performed. An energy model of the energy consumed by the sensor nodes is presented and analyzed. The result of the analysis provides an accurate identification of the main energy consumers, the magnitude of their consumption and an in-depth understanding of the key mechanisms that need to be applied to improve energy efficiency in wireless sensor nodes. The emphasis is on the presented energy efficient protocol. Three action scenarios from the sensor nodes are presented, outlining the main guidelines and strategies for improving the efficiency of the wireless nodes. In addition, the research results reveal the magnitude of energy savings that can be achieved by implementing the improved duty cycle mechanisms in wireless sensor nodes.

A wireless level sensor system was designed aiming at solving data acquisition issues on material level measurement of alumina storage bin towers. Using the high performance MCU, STM32, and 433MHZ wireless communication modules, the wireless nodes were developed. New measuring method based on weighing sensors was proposed to adapt to the severe environment of storage bins full of thick dusts and high-density magnetic field. Experiments and actual measurement in factory environment were performed and indicated the stability and reliability of the wireless material level measuring system.

The main objective is to achieve networking integration with a wide range of interconnected information space and depth of the physical world, and wireless sensor networks as a peripheral network of things, it is possible on a larger spatial and temporal scale networking provides active physical perception of things It means the world. Wireless sensor network nodes with limited energy characteristics, and data transmission is the main source of energy consumption in wireless sensor nodes, on the other hand, the presence of Things pressing needs in terms of real time, and data transmission scheduling strategy is the impact of network transmission One of the main factors in the delay, therefore, has important practical significance to study wireless sensor network transmission and storage technologies. In this paper, based on Hadoop HBase is a distributed database that provides real-time read and write, random access, high scalability and high availability storage services. Use HBase to build two storage architectures, metadata are stored within the area sensor data and sensor data.

Problem statement: Power consumption was one of the most challenging aspects to design low power wireless sensor nodes. The objectives of the study were to (i) Design low voltage, low power transmitters for wireless sensor nodes and (ii) Compare and analyze the performance of the transmitters. Approach: The transmitters employed direct digital modulation scheme to reduce the power consumption of the sensor nodes. Emphasis was placed on observing device reliability constraints at low power to maximize the life time of the wireless sensor nodes. Results: The Amplitude Shift Keying (ASK) transmitter consumed a power of 400.104 μw from the 1.2 V supply. The Frequency Shift Keying (FSK) and Phase Shift Keying (PSK) transmitters consumed 520 μw and 5.2 mw respectively at 2.4 GHz. The transmitters suitable for low voltage, low power wireless sensor nodes were designed and implemented in 120 nm CMOS technology Conclusion: The performances of the ASK, FSK and PSK transmitters were analyzed and were compared with the previously reported low power approaches operated in similar frequency ranges.

Internet Protocol version 6 (IPv6) over Low-power Personal Area Network (6LoWPAN) is proposed by the Internet Engineering Task Force (IETF) working group to accomplish the concept of IP-based Wireless Sensor Network (WSN). A new layer is incorporated between IPv6 network layer and 802.15.4 MAC layer, which is entitled adaptation layer. Header compression, packet fragmentation, and layer two forwarding are the main tasks of the adaptation layer. An IPv6 packet is too big regarding to the Maximum Transmission Unit (MTU) size of 802.15.4 standard thus it has to be fragmented. Breaking up a big packet to number of small fragments and attaching new headers to each fragment may affect the energy level. In this paper, we place an attention on the impact of the adaptation layer on the energy consumption of a 6LoWPAN sensor node. From our analysis, we found that the adaptation layer, in particular the fragmentation process may increase the energy consumption of a sensor node by 5 to 10 percent.

the wireless sensor network technology emerged in the late 1990s, since then it has spread across a wide range of potential applications to industry, science, transportation, civil infrastructure, and security. Main research efforts in the wireless sensor network field focused on achieving the desired performance requirements and reducing the energy consumption to the least possible. This survey paper introduces some of the most recent research outcomes on the energy consumption of wireless sensor networks.

With the miniaturization of electronic devices, small size but high capacity power supply system appears to be more and more important. A hybrid power source, which consists of a fuel cell (FC) and a rechargeable battery, has the advantages of long lifetime and good load following capabilities. In this paper, we propose the schematic of a hybrid power supply system, that can be integrated on a chip compatible with present CMOS process. Besides, considering the problem of maximizing the on-chip fuel cell's lifetime, we propose a modified dynamic power management (DPM) algorithm for on-chip fuel cell based hybrid power system in wireless sensor node design. Taking the wireless sensor node powered by this hybrid power system as an example, we analyze the improvement of the FC-Bat hybrid power system. The simulation results demonstrate that the on-chip FC-Bat hybrid power system can be used for wireless sensor node under different usage scenarios. Meanwhile, for an on-chip power system with 1cm2 area consumption, the wafer-level battery can power a typical sensor node for only about 5 months, while our on-chip hybrid power system will supply the same sensor node for 2 years steadily.

The rapid development of the agricultural Internet of Things (IoT) is inseparable from the support of wireless sensor networks (WSNs) in recent years. To further facilitate the adaptation of WSNs to agricultural applications, reducing the energy consumption of sensor nodes in agricultural environments has become a crucial problem. Sleep scheduling in randomly deployed WSNs is an effective method to reduce the energy consumption of sensor nodes, which can extend the network lifetime while ensuring network coverage. However, most of the existing sleep scheduling algorithms require frequent information exchange (such as broadcasting to find neighboring nodes and collecting nodes’ residual energy), which will inevitably lead to massive energy consumption. To address this problem, in this article, an unmanned aerial vehicle (UAV)-assisted sleep scheduling algorithm (UAVSS) is proposed, which avoids excessive information exchange among nodes and ensures sufficient network coverage with the least number of sensor nodes. The UAV traverses all the sensor nodes along the shortest path to help information exchange and gather sensing data. Furthermore, the UAV path is planned by using the latest monarch butterfly optimization (MBO) algorithm. Simulation results indicate that the proposed UAVSS can prolong the network lifetime while ensuring the required area coverage.