Abstract:Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today's communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given.

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Range-free localization algorithm continues to be an important and challenging research topic in anisotropic Wireless Sensor Networks (WSNs). Designing range-free localization algorithms without considering obstacles or holes inside the network area does not reflect the real world conditions. In this paper, we have proposed Detour Path Angular Information (DPAI) based sensor localization algorithm to accurately estimate the distance between an anchor node and a sensor node. We utilized the Euclidean distance and transmission path distance among anchor nodes to calculate the angle of the transmission path between them one by one. Then the estimated hop distance is adjusted by the angle between the anchor pairs. Based on the angle of the detoured path (which is the key factor for accuracy), our algorithm determines whether the path is straight or detoured by anisotropic factors. Our proposed algorithm does not require any global knowledge of network topology to tolerate the network anisotropy nor require high sensor node density for satisfactory localization accuracy. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis. DPAI achieved average sensor localization accuracy better than 0.3r in isotropic network and 0.35r in anisotropic network when the sensor density is above 8

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Background How the informal providers deliver health services are not well understood in Bangladesh. However, their practices are often considered inappropriate and unsafe. This study attempted to fill-in this knowledge gap by exploring their perceptions about diagnosis and appropriate treatment, as well as identifying existing barriers to provide appropriate treatment. Methods This exploratory study was conducted in two peri-urban areas of metropolitan Dhaka. Study participants were selected purposively, and an interview guideline was used to collect in-depth data from thirteen providers. Content analysis was applied through data immersion and themes identification, including coding and sub-coding, as well as data display matrix creation to draw conclusion. Results The providers relied mainly on the history and presenting symptoms for diagnosis. Information and guidelines provided by the pharmaceutical representatives were important aids in their diagnosis and treatment decision making. Lack of training, diagnostic tools and medicine, along with consumer demands for certain medicine i.e. antibiotics, were cited as barriers to deliver appropriate care. Effective and supportive supervision, training, patient education, and availability of diagnostics and guidelines in Bangla were considered necessary in overcoming these barriers. Conclusion Informal providers lack the knowledge and skills for delivering appropriate treatment and care. As they provide health services for substantial proportion of the population, it’s crucial that policy makers become cognizant of the fact and take measures to remedy them. This is even more urgent if government’s goal to reach universal health coverage by 2030 is to be achieved. Electronic supplementary material The online version of this article (10.1186/s12913-019-4254-3) contains supplementary material, which is available to authorized users.