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With the increasing tendency of incorporating technology into environments and activities in everyday life, new methods are being proposed to better integrate devices and mankind. Networks designed for monitoring areas through video and image systems are being implemented in several applications.Recent studies have shown interest from both the academy and industry to integrate wireless surveillance networks with low-cost and long range transmission technologies, such as LoRa (Long Range). With the intention to explore this topic, this work presents the development of a system prototype for intelligentmonitoring as a basis to future implementation of low-cost LoRa-based Wireless Image Sensor Networks (WISN). The system developed consists of a processing unit, a data routing interface and multiple sensor nodes. Its operation is autonomous and initiated through the detection of human presence, by the sensornode, capturing an image of the individuals present at each detection. The data is transmitted through LoRa devices to the central hub, where python-based methods of facial detection and recognition are employed. Several tests were performed to both adjust the system and to verify its efficiency. The results achievedwere satisfactory, indicating the viability of the proposed low-cost LoRa-based WISN.

International audience; Wireless Image Sensor Networks (WISN) where sensor nodes are equipped with miniaturized visual CMOS cameras to provide visual information is a promising technology for situation awareness, search&rescue or intrusion detection applications. In this paper, we present an off-the-shelf image sensor based on Arduino boards with a CMOS uCamII camera. The image sensor works with raw 128x128 image, implements an image change detection mechanism based on simple-differencing technique and integrates a packet losstolerant image compression technique that can run on very limited memory platforms. We detail the performance and energy consumption measures of the various image platforms and highlight how both medium-end and low-end platforms can be supported. From the single-camera system, we describe the extension to a multi-camera system which provides omnidirectional sensing at a very lost cost for largescale deployment.

Wireless sensor networks are increasingly gaining attention. In recent years, a great deal of monitoring, control and tracking applications have been designed for different scenarios. For such networks, camera-enabled sensors can retrieve visual data from a monitored field, providing valuable information for many applications. In general, those networks have resource constraints of processing, memory, energy and transmission bandwidth, imposing many design challenges. Nevertheless, a group of applications may also have security requirements, which bring additional complexity to be handled. Most traditional security mechanisms for popular networks, like the Internet, are not suitable for wireless sensor networks, demanding proper investigation in this area. In this paper, we survey recent developments in encryption and privacy in wireless sensor networks deployed for transmissions of image snapshots, reviewing innovative approaches to provide different levels of security. Promising research directions are also discussed.

When camera-enabled sensors are deployed for visual monitoring, a new set of innovative applications is allowed, enriching the use of wireless sensor network technologies. In these networks, energy-efficiency is a highly desired optimization issue, mainly because transmission of images and video streams over resource-constrained sensor networks is more stringent than transmission of conventional scalar data. Due to the nature of visual monitoring, that follows a directional sensing model, camera-enabled sensors may have different relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view. Exploiting this concept, each data packet may be associated with a priority level related to the packet's origins, which may be in turn mapped to an energy threshold level. In such way, we propose an energy-efficient relaying mechanism where data packets are only forwarded to the next hop if the associated energy threshold level is below the current energy level of the relaying node. Thus, packets from low-relevant source nodes will be silently dropped when the current energy level of intermediate nodes run below the pre-defined thresholds. Doing so, energy is saved potentially prolonging the network lifetime. Besides the sensing relevancies of source nodes, the relevance of DWT subbands for reconstruction of original images is also considered. This allows the creation of a second level of packet prioritization, assuring a minimal level of image quality even for the least relevant source nodes. We performed simulations for the proposed relaying mechanism, assessing the expected performance over a traditional relaying paradigm. (41 refs)

Energy consumption is a critical problem affecting the lifetime of wireless image sensor networks (WISNs). In such systems, images are usually compressed using JPEG standard to save energy during transmission. And since DCT transformation is the most computationally intensive part in the JPEG technique, several approximation techniques have been proposed to further decrease the energy consumption. In this paper, we propose a low-complexity DCT approximation method which is based on the combination of the rounded DCT with a pruned approach. Experimental comparison with recently proposed schemes, using Atmel Atmega128L platform, shows that our method requires less arithmetic operations, and hence less processing time and/or the energy consumption while providing better performance in terms of PSNR metric.