外文翻译-基于GPS的动物跟踪系统

中文5790字
基于GPS的动物跟踪系统
1摘要：
野外感知系统是一种用于监测沼泽鹿行为和迁徙模式的无线传感网。

该系统将收集微气候以及动物的位置信息，并将这些信息以数据流的方式使用点对点网络传达到基站。

基站使用网关，将收集到的所有数据上传到互联网上的一个数据库和用基于可视化软件的浏览器将这些信息描绘出来。

每一个点将显示五个信息，即：位置（用GPS），温度，湿度，前进方向和环境亮度。

此外，该节点将有一个实时时钟同步网络和保持时间信息。

一个外部数据闪存空间将会用于记录从传感器和网络节点上获取的数据。

无线电收发机通过点对点的通信协议将数据传送到基站。

一个太阳能接受系统为电池提供节点能量，用于延长节点的寿命。

这个系统将会被做成项圈的形式，这样能比较容易的套在动物的脖子上。

关键词：GPS跟踪；野外感知系统；无线传感网，野生动物跟踪，微型气候感知器
I.前言
无线传感器网络(WSN)总是使用从分布式自治节点空间获得的感知。

把微型传感器、微控制器、无线电收发机和一种带有电源,低功耗和廉价的传感器节点(我们将简单地称之为节点)结合可以用于监视物理或环境的条件,如不同位置上的温度、声音、振动、压力、运动等。

对于正在移动的节点这个任务将变得更具挑战性。

工程所要进一步研究的问题是如何使节点的电力供应足够维持到最后一年。

这篇文章的重点就是如何通过对数据的处理，改善无限传感网的设计来突破无限传感网在能量方面的束缚。

过去已经见过各种各样的无线传感器网络应用于栖息地监控、地震检测,环境监测、健康系统监统等,这些领域很少会遇到移动节点,动态网络拓扑,通信失败,电力供应有限,恶劣的环境条件变化等情况。

为了从对野生动物监测中寻到解决问题的方法和了解动物与其周围环境的复杂的关系,科学家必须亲自到现场去收集所需要的数据。

在某些情况下将无线电发射机安置动物身上能让研究变得更加容易,但是图像的大部分仍然不能被标记出来，因为缺少有效的数据收集。

有许多理由去解释为什么频繁的到现场去做调查是困难和不明智的。

首先,研究物种时要做到完全避免人类干扰几乎是不可能的。

人类频繁的访问或打扰已潜移默化中对物种产生了影响[1]。

其次,在晚上追踪活动的动物与其说是做实验或做研究还不如说是冒险。

最后, 如果不使用专用的低成本传感器网络设备。

它
1作者Vishwas Raj Jain, Ravi Bagree, Aman Kumar, Prabhat Ranjan；出处 Intelligent Sensors, Sensors Networks and Information Processing,2008.ISSNIP 2008.
不仅费时而且需要花费大量的资金来跟踪动物迁移以及其饮食习惯。

因此就需要一个自动化的系统,带有拥有众多网络传感器节点的自然空间能够长时间的收集数据(即使在夜间)、如果没有这样的系统，靠人工检测，则研究范围和结论的准确率则非常有限。

它还能够在不对生态造成干扰的情况下收集数据和相比传统研究方式来说，它是一种更为经济方法来进行长期的研究。

一些监控野生动物运动和习性的先进理念曾做过尝试，如斑马网络[2]和伟大的鸭子岛实验[1]。

通过以上经验的学习，我们可以知道生物感知网络的构建也是出于同样的出发点。

它是拥有更低能耗,更大的范围、更加多样的环境感知特性和更健壮数据备份的系统。

野外感知系统是一个用于监控沼鹿(泽鹿)行为和迁移模式的无线传感器网络系统。

该系统对于那些中型或大型的物种同样适用。

这个系统中配有GPS、无线收发器和其他各种传感器、硬件为支持野生动物监控的需要而设计的。

捕获的数据可以提供给野生动物研究人员让他们完成研究和学习的目。

它将有助于他们理解濒危物种的需求,以及这些物种与周围的环境关系。

本文在节点，基地，网络的水平上探讨了野外感知系统的硬件和软件设计的体系结构。

特别是它把设计和测试系统时遇到的问题也体现了出来。

II.基于GPS的动物跟踪系统
生物传感网是一种试图让研究人员了解更多有关沼鹿的生活习性的途径。

输入的该系统的设计要有哪些功能由野生动物研究人员输入。

这个系统计划将带有传感器的轻质项圈安放在动物的脖子上。

这个项圈会从附近动物中收集到科学研究所需要的数。

将收集到的有用数据数据发送到其他节点或基站, (基站越来越偏好的情况下两者都是可用)。

这个系统的主要的功能是使用GPS跟踪动物的迁徙运动。

要获取的数据除了位置信息,还包括动物的生活习性和它的周围环境参数。

也可以说成是一项对动物的活动的研究。

动物的生活模式需要被记录下来。

自从监测区域变大后,获得的数据需要不断的从一个节点传到另一个节点依据直到它转移到一个基站。

最后系统需要运行持续至少12个月,因此电源设计和使用需要优化
位置记录: 在监测动物的迁移模式时，GPS需呀能够精准的定位。

研究人员指定的位置每3个小时能发生三次GPS位置信息就足以绘画出这个动物的近一年的运动轨迹
周围环境:由于在过去的一年里沼鹿的迁徙受地面植被的覆盖率的影响,所以研究人员还需要监控动物的居住和觅食环境。

用于测量温度、湿度,和光线以及动物活动的传感器也同时安装在了系统里。

数据传输和恢复: 分散的数据只有在被传播到基站(s)的情况下才能被科学家收集起来用于分析。

因为沼鹿的活动范围相当的大，所以不可能在它们的整个活动地区安装众多基站。

为了解决这个问题,我们需要通过移动网络,采用点对点通信方式是试
图在无线卡插槽上传输数据[2]。

为了弥补时间上的延迟,节点上安装了一个较大的外部flash用来容纳数据在节点上的生成时间以及传输过程中获取的时间。

3.1节讨论更详细的讨论了数据的交流问题。

能量获取:每一个检测点都必须工作最少一年,用于追踪迁移路径,避免人为干预。

他们与其他节点唯一的连接是通过无线链接或基站。

而且,由于在节点的重量上有一个限制,就不能提供一个巨大的电源供应。

因此,节点需要轻量级电力备份系统。

鉴于这种动物大部分在露天的环境下活动,所以可以通过太阳能来给系统提供电力供应。

只要认真落实能源采集，补充的管理政策,能源的需求容易得到满足。

能源的提供将会在3.3节更详细地讨论
III．系统概述
大体上生物传感网系统分为如图1所示的几个部分,即硬件、相关系统软件和驱动器,中间设备服务器连接数据记录和web主机服务设备最后基于浏览器的可视化软件。

图1 生物传感网系统概述
1)硬件架构
完整的传感器节点连同电池充电系统的是以一个项圈的形式呈现的，它被套在了沼鹿的脖子上。

生物传感网节点的硬件系统的体系结构如图2所示。

图2 硬件设计框架 为了满足在准确性、能量、电压兼容性和成本方面的考虑[6]，每个组件都在原来的基础上经过了精心挑选。

这个组件由如下的一个单个节点组成:
微控制器——ATMega1281V[7],128 k 字节程序内存,是核心处理单元的设计。

它有4 k 字节的eepm 和8 k 字节的存储器。

有两个可独立使用的串口。

GPS 和无线电收发机的通信与核心处理单元同步。

这使我们能够消除软件章节
3.2节描述的多路复用的开销。

当连续通信是，内部谐振器是不够准确，这时需要在外部加上一个1.83728 MHz 的晶振。

(限制波特误差百分之零[7])。

实时时钟——DS3231[8]——为了能够使所有的节点在同一个时间启动以达到同步。

外部RTC 必须准确将这些节点同步。

它还产生周期性的中断来将微控制器从―断电‖睡眠模式中唤醒。

高度的准确性,集成的温度测量使设备的晶体振荡器(TCXO)、I2C 接口在不同的波特率工作时仍能适合这一应用。

系统中在时间上的任何不匹配(在两个交互节点)将会花费大量的电力在网络的同步上。

由于运行环境的不同，RTC 在不同的节点上运行是有偏差的。

为了维护节点与节点之间通信的准确性,RTC 与GPS 设备每五天实现一次同步,保持1秒内的时钟偏差。

GPS -拉森IQ GPS 接收机与天线[9],它有封装小、处于工作模式的时候能耗低(89兆瓦为3.3 v)。

为了达到较高的精度,它使用十二处理渠道来跟踪GPS 卫星信号。

拉森IQ GPS 支持NMEA 协议的GPRMC 通信形式。

这一通信协议包涵了所有需要的内
容，即日期、纬度、经度和时间。

它与单片机通信频率为4800个bps。

自其读数开始，GPS每3小时会自动转换开/关模式。

为了利用GPS的―热启动‖功能,我们使用一个电池备份机制。

无线电收发机——XBee-Pro[10]——这个数码网络关键
通信模式是基于IEEE 802.15.4 ZigBee /标准。

它运行在2.4 ghz ISM波段(只有在印度免费提供),通信距离超过一公里。

然而和900 MHz相比，传输距离相同是，这个频率导致更高的能源消耗,我们得使用更高的数据频率和更小型而紧凑的天线。

低成本、低功耗和易用性也是其优势。

它还提供了五个睡眠模式来满足不同应用场合的需求。

当它仅是一个供电系统而不使用其时间功能时，我们用最低功率的睡眠模式。

几毫秒的延迟对于系统来说是允许存在的。

内存——爱特梅尔公司AT45DB16B数据flash[11]，我们需要一个大的内存存储空间来弥补基站与节点之间通信的延迟。

对于我们的无线传感器网络,一个节点需要收集的数据来自同行,这要求更高内存容量。

AT45DB16B拥有SPI接口正好符合了这一要求。

基于UCBs环球文件系统[13]的可操作的内部开发文件系统[12], 的使用,这使得存储系统简单和高效。

附加的传感器,为了收集沼鹿周围环境的参数，从大鸭岛上的经验试验[1]中得知我们需要在节点上安装数字传感器。

湿度传感器有内置的加热器用于蒸发吸收水。

Sensirion SHT11的[14]传感器是一个数字温度和湿度传感器(分辨率:0.01°C和0.05% RH)的组合。

这传感器是被一个盖帽(IP67标准)遮着，使其感知环境的同时达到保护它的作用。

我们使用一个TAOS的TSL2561t[15]这是一款高灵敏度的数字光传感器。

为了监控动物的活动我们使用了飞思卡尔半导体的MMA6270QT[16]模拟加速度计。

这些拥有位置信息的数据为更加深入的了解沼鹿的迁移模式及与气候的变化。

节点的设计采用大量的减少噪音的技术。

为了降低ADC的噪声，一个LC滤波器（L =10MH和C=0.1μF的）已被添加到的ADC引脚的微控制器。

此外，为了减少噪音[6]，A VCC被连接到主电源供应系统且没有任何扇区出线。

整个PCB敷铜用以使噪声保持在最低水平，同时还消散节点产生的热。

如图3所示。

节点的大小为5×6平方厘米，仅重34gms。

包括电源（LIION电池与太阳能充电机制）体系的总重量为，
（a）（b）
图3 （a）顶视图（b）底视图
2）软件架构
设计主要解决的是问题是能源，wildCENSE软件工具的有效的调度和事件同步。

节点大部分时间都保持在休眠/无效模式。

以一个产生周期性中断的实时时钟（RTC）为基础，从的传感器和GPS上收集所需的数据。

准确性的RTC有助于实现节点到节点，或节点与基地之间信息的同步。

GPS每3小时发送一次数据，并安设定好的每十分钟唤醒相应的传感器。

无线收发机，GPS和外接存储器都有独立的端口，即USART0，USART1，SPI，我们都能同时使用它们。

当GPS处于开机状态，并在修理的过程，如果附近有节点/基站则可以无线电进行数据的传输。

当前读/写数据段的指针存储在微控制器的EEPROM。

这的优点是在重新启动的情况下，（如看门狗复位），数据段指针可以从EEPROM中重新获取，
一旦发现了节点/基站，所以得节点会在相同的时间开启和并同时进行数据交换。

成功转移到所述基站的数据是将会从节点中删除。

微控制器和无线收发信机之间的通讯波特率被设置为57600，虽然这个无线电收发机也支115200的波特率。

我们的测试结果表明，在较低的波特率（57600）数据有更好的可靠性，因此使用了这以波特率。

3）系统能源管理
WSN的能源需求是设计时要考虑的最最关键的要素。

当权衡节点的重和它的能量所需时，野生动物监测方案变得更具挑战性。

在本节中，我们将在软件和硬件水平上讨论我们的能源管理技术，和野外感知体系。

图4中所示的是一个节点能源消耗的比例图。

能量的具体消费计算在本节C部分。

图4 野外感知系统节点的功耗必比例图
A.硬件级别的能源管理
理想的检测节点包涵一定数量的传感器沿与其他外围设备，如RTC，外部闪存和无线电收发信机。

为这样复杂的系统设计一个简单的电源供应器是一个巨大的挑战。

所有组件和传感器都经过精心挑选，都是低功耗以及几乎相同的输入电压范围3.3V。

该系统是由一个可再充电的锂离子电池供电，它可以安全地电压范围为2.7 V至4.2 V。

太阳能发电被附加上去以便进一步增强节点的寿命。

此外，未用引脚和数字输入缓冲器分别被配置成输出引脚和禁用，最大限度地减少他们的能源泄漏。

使用一个共同的电压（3.3V）的决定不仅是为了节点电压设计的简单，同时也能够节省那些浪费在不同的电压调节上的能量。

为了最大限度的利用电池的能量，一个DC / DC转换器，德州仪器（TI）[17]的一款降压升压器TPS63001被使用。

它可提供恒定的输出电压3.3V 的最大输出电流1.8A;转换效率高达96％。

B.软件级别的能源管理
当节点处于非活动状态时，野外感知系统采用微控制器的―关机‖睡眠模式，从而节省了大量的能源。

另一种方法是使用双时钟方案，而不是睡眠模式，但是使用外部实时定时器时钟的同时，我们仍能够通过它自身的掉电模式功能节省能源。

这个断电模式的特点是把所有的一切都关机，并且通常包括时钟源[7]，在3.3V的电压下消耗的电流小于10uA的―看门狗‖。

掉电检测器是在睡眠模式状态状态下[18]唯一工作的模拟量模块。

但是，因为自从该模块在我们的设计中不需要以后，我们已经把它永久关闭，确保进一步降低―断电‖睡眠模式的供电。

在处理和读取传感器时需要较小的延时，这个时候另一个节省功耗的模式，―省电‖睡眠模式将被使用。

随着微控制器，其他外围设备也提出休眠模式，以最大限度地减少能源的使用。

当节点是在睡眠模式时GPS被关闭。

这是通过电源开关TPS2092[19]来实现的，。

应用程序不是每时每刻的使用使我们有机会让无线收发器处在最低功耗模式下，这一模式的功耗不到其他模式1/5。

C.节点寿命估算
表1说明了节点上的各个组件的电力需求。

以下假设
是基于每个节点的组件能工作最低一年：
•节点每3小时进行测量。

•假设，大部分的时候，沼鹿活动在露天的环境里，可得到一个明确的GPS位置信息。

•每隔一小时，节点通过RTC同步试图与其他节点/基地进行联系，。

•只有70％的锂离子电池的能量已经假定可用[20]。

•最后，我们假设一个节点，每天会从其他节点收到最多7页数据并想其他节点发送
一页的转换数据。

在一个月的时间里，该节点把它的所以数据都传输给基站。

按上述的假设和使用所述的硬件，每个节点每天需要13.5mAh能量或7040mAh 一年。

为了满足上述要求，锂离子电池包8Ah的容量是足够的。

太阳能充电可进一步延长节点的工作时间。

在表1中，我们将用―TX‖代表发送模式，―RX‖代表接收模式和―PD‖代表断电模式。

―组件在不同模式下的平均电流（以毫秒安培）的要求在第4栏给出。

第5列―T‖给所采取的传感器及其它外设单次读出的典型时间（单位为秒）。

最后一列，即―C‖是在不同的模式下各个组件每天的电流需求（mAh）。

表1 节点寿命估计
IV 总结
本文提出了一种用于监测野生动物的无线传感网操作原型。

野外感应是一种紧凑，准确，高效节能的感应。

除了高效节能，它还提供详细的位置信息且拥有非常高的精度。

软件协议和硬件实现都经过精心设计，以实现优化系统能源的要求。

虽然GPS和无线电收发器等单元要消耗相当大的能源，但是利用太阳能充电机制，节点寿命将大为提高。

英文原文：
wildCENSE: GPS based Animal Tracking System
Abstract—wildCENSE is a Wireless Sensor Network (WSN) system which attempts to monitor the behaviour and migration patterns of Barasingha (Swamp Deer). The system would collect the micro-climatic as well as positional information of the animal and communicate it to a base station through flooding of data using peer-to-peer network. The base station, using a gateway, upload all the collected data to a database server on Internet and portray the information using browser based visualization software. Each node would monitor five parameters namely position (using GPS), temperature, humidity, head orientation and ambient light. Also, the node will have a real time clock for
the synchronization of the network and to keep timing information. An external data flash memory would be used to record the data collected from sensors and other peer nodes. A radio transceiver would transmit the data to the base station by using a peer to peer communication protocol. A solar energy harvesting system for recharging node’s po wer supply batteries is being added to prolong the lifetime of nodes. The system would be integrated in the form of a collar that can be easily fitted on the neck of animal.
Keywords- GPS Tracking; wildCENSE; micro-climate sensing; Wireless Sensor Networks; wildlife tracking
I. INTRODUCTION
Wireless sensor networks (WSN) invariably employ sensing from spatially distributed autonomous nodes. With a little jugglery of sensors, micro-controllers, radio transceiver and an energy source, low-power and inexpen sive sensor nodes (we’ll simply call them nodes) can be made to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion etc. at different locations. The task becomes more challenging when the nodes are mobile. To further question the engineering effort is the case, where the node’s power supply should be sufficient for it to last years. Hence the acquisition, accumulation and relay of data impose a great challenge on the WSN's design viz. the strict energy constraints.
The recent past has seen a wide variety of WSN applications namely Habitat monitoring, Seismic Detection, Environmental monitoring, Health monitoring systems etc., of which mobile nodes, dynamic network topology, communication failure, limited power supply, harsh environmental conditions are few of the varied challenges.
To address the issues in wildlife monitoring and to understand the complex
relationship of animals with their surrounding, scientists had to collect the required data manually by visiting the site. In some cases the search was made easier by tagging the animal with radio transmitters to relocate them easily, but yet the seemingly bigger part of the picture remained un-addressed: the efficient data collection. There are numerous reasons why it is difficult and not advisable to visit the site frequently. Firstly, studying the species without avoiding human contact is almost impossible. Frequent human visits or disturbances affect the species in ways unknown [1]. Secondly, keeping track of animal activity in the dark after dusk become more of an adventure than an experiment or a study. Finally, it is not only time consuming but also money intensive job to keep track of animal migration as well as its feeding habits without using dedicated low cost sensor networking equipments.
An automated system would thus be desired, equipping natural spaces with numerous networked sensor nodes to enable long-term data collection at times (even at night), scales and resolution which are very difficult if not impossible, to achieve by manual monitoring. It also allows collecting data without disturbing the ecology and yet represents a substantially more economical method for conducting long-term studies than traditional one. Significant proofs of concepts and previous attempts to monitor wildlife movement and habitat have been made like the ZebraNet [2] and Great Duck Island Experiment [1]. Learning from the experiences of the aforementioned, wildCENSE is an attempt on the same footprint, designed to have lower power consumption, better range, varied environment sensing features and more robust data backup system.
wildCENSE is a WSN system which attempts to monitor the behavior and migration patterns of Barasingha (Swamp Deer). System being designed can be suitable for many more species of medium to large size. Equipped with a GPS, Radio transceiver and various other sensors, the hardware is designed to support the needs of wildlife monitoring. The captured data can be provided to the wildlife researchers for their research and study purposes. It will be helpful to them to understand the needs of the endangered species, and the relationship these species share with the surroundings.
The paper fundamentally discusses the hardware and software design architecture of the wildCENSE system at the node, base and network levels. In particular, it embodies the issues and constraints, which were met during the design and testing of the system.
II. GPS BASED ANIMAL TRACKING SYSTEM
The Barasingha is native to India and Nepal. Once it populated throughout the basins of the Indus, Ganges and Brahmaputra rivers, as well as parts of central India reaching out till the river Godavari. But in past few decades its population has declined significantly
listing them as endangered species by IUCN from 1984 to 1996 and as vulnerable since 1996 [4]. Wildlife researchers while surveying Jhilmil Tall (Uttaranchal) area came across some 30 heads of the Barasingha on February 3, 2005 [5]. Trails indicate that they might have migrated across the Nepal border. But yet their exact migratory path is unknown; hence it is important to monitor their movement and protect them. wildCENSE is an attempt towards discovering this path along with helping the researchers know more about their habitat. The input for the design of the system came from wildlife researchers. In the system proposed, specially designed light-weight collar, with sensor node attached, would be put on the animal. These collars would collect data about the desired parameters from the vicinity of the animal. The data may then be sent to other nodes or the base station, depending on the availability of either (base station getting a preference in case of both being available).
The prime requirement is to track the migratory movement of the animal which is done using a Global Positioning System (GPS). Besides the location, the animal's habitat and its ambient environment parameters are of interest. Also a study of the animal’s activities viz. the grazing patterns of the animal needs to be recorded. Since the area under surveillance is large, the acquired data needs to be propagated on a node to node basis until it is transferred to a base station. Lastly the system needs to run continuously for a minimum of 12 months, so the power supply design and its usage need optimization.
Positional Logs: The GPS reading needs to be accurate and precise, in view with the migration pattern of the animal. As researchers specify, a location reading every 3 hours would be enough to draw a close enough movement track of the animal over a year.
Ambient Environment: With the animal covering a lot of ground during its migration over the year, the researchers also need to monitor the environment in which the animal dwells and grazes. Sensors for measuring the temperature, humidity, and light as well as animal activity are embodied in the system.
Data Transmission and Recovery: To collect the dispersed data for analysis by the researchers, it needs to be transmitted to the base station(s). Since the Barasingha has a fairly large movement track it is not possible to equip the entire region with numerous base stations. To address this issue, the data needs to be moved through the network, employing node to node communications as was attempted in Zebranet[2]. In order to compensate for high latency, the node has a large external flash to accommodate data generated on the node as well as acquired through peer interaction. Section 3.1 discusses the communication in more detail.
Energy harvesting: The nodes need to be alive for a minimum of a year, tracking the
migration path, avoiding any human intervention. Their only contact is the wireless link with other nodes or the base station as the case may be. Also, since there is a limitation on the weight of the node, a bulky power supply is forbidden. Hence, the node needs to have lightweight power back up system. Given that the animal will mostly be in large fields under open skies, the required power supply could be equipped with solar energy harvesting features. With careful energy management policy, supplemented by harvesting, the energy requirements can be easily met. The power supply is discussed in more detail in Section 3.3
III. System Overview
Broadly the wildCENSE system is divided as in Figure 1, namely the hardware, related system software and drivers, middleware servers with data logging and web hosting services and finally the browser based visualization software.
1) Hardware Architecture
The complete sensor node along with the battery recharging system is in the form of a collar to be worn by the animal. Hardware system architecture of wildCENSE node is as depicted in Figure 2. The design issues as discussed in Section 2 have been carefully met.
Each component has been carefully selected based on earlier prototypes to meet accuracy, power, voltage compatibility and cost considerations [6]. The components that make up a single node are as follows:
Micro-controller – ATMega1281V [7], with 128K bytes program memory, is the core processing unit of our design. It has 4K bytes of EEPROM and 8K bytes of SRAM. The availability of 2 USART ports enables independent
Figure 1. wildCENSE System Overview
communication of GPS and Radio transceiver with the core processing unit simultaneously. This allows us to remove the multiplexing overhead as described in the software section 3.2. The internal resonator is not accurate enough for serial communication, so an external crystal of 1.83728 MHz is used. (limiting baud error to zero percent [7]).
Real Time Clock - DS3231 [8] - For node discovery, all the nodes need to wake up at the same time requiring them to be synchronized. External RTC is required to accurately synchronize these nodes. It also generates periodic interrupts to wake up the micro-controller from its ―Power Down‖ sleep mode. Features like extreme accuracy, integrated temperature compensated crystal oscillator (TCXO), I2C interfacing at different baud rates make the device ideal for this application. Any mismatch in the time in the system (between two interacting nodes) can cost a lot of power in network synchronization. RTC running on different nodes are skewed due to the environment. To maintain the accuracy of node to node communications, the RTC is synchronized by the GPS device every five days, keeping the clock skew within 1 sec.
GPS – Lassen iQ GPS Receiver with antenna [9] – It has a small footprint, low energy consumption (89mW at 3.3V) in active mode. To achieve high accuracy, it uses twelve processing channels to track the GPS satellite signals. Lassen iQ GPS supports the required
NMEA protocol with GPRMC message format, which contains all the required information namely date, latitude, longitude and time. It serially communicates with the microcontroller at 4800 bps. Our GPS is used in On/Off mode since readings are taken every 3 hours. To utilize ―Warm start‖ feature of GPS, we use a battery backup mechanism.
Radio Transceiver – XBee-Pro [10] -This Digi-Key communication module is based on ZigBee/IEEE 802.15.4 standard. It operates at 2.4GHz (only freely available ISM band in India), providing a range of more than a kilometer. While using this frequency results in higher power consumption for same range compared to 900 MHz, we gain in terms of much higher data rate and smaller compact antenna.
Low cost, low power and ease of use are among the other advantages. It also provides five sleep modes to meet various needs of different applications. We use lowest power sleep mode as it is not a time but power critical system. Delay of few milliseconds of wake up are well within the system’s tolerance
Figure 2. wildCENSE Hardware setup depicting various components, their interfacing and power supply.
Memory – ATMEL AT45DB16B Data flash [11] A high memory storage is required to complement the long latency of communication between the base and the node. For our WSN, a node needs to collect data from its peers, asking for a higher memory capacity. AT45DB16B, with SPI interfacing looks quite promising for the scenario. An operational in-house developed file system [12], based on UCBs Matchbox file system [13], is being used, which makes the storage system simple and efficient.
Additional sensors - To collect the ambient environment parameters of the animal, the node mostly incorporates digital sensors, as from the experiences of Great Duck Island。