当物联网与大数据牵手成功，会发生什么？
相比传统的互联网，在物联网中，对大数据技术具有更高的要求。
物联网的最主要特征之一是节点的海量性，除了人和服务器之外，物品、设备、传感网等都是物联网的组成节点，其数量规模远大于互联网;同时，物联网节点的数据生成频率远高于互联网，如传感节点多数处于全时工作状态，数据流源源不断。
物联网中数据海量性必然要求骨干网汇聚更多的数据，数据的传输速率要求更高，同时，由于物联网与真实物理世界直接关联，很多情况下需要实时访问、控制相应的节点和设备，因此需要高数据传输速率来支持相应的实时性。
物联网涉及的应用范围广泛，从智慧城市、智慧交通、智慧物流、商品溯源，到智能家居、智慧医疗、安防监控等，无一不是物联网应用范畴;在不同领域、不同行业，需要面对不同类型、不同格式的应用数据，因此物联网中数据多样性更为突出。
物联网是真实物理世界与虚拟信息世界的结合，其对数据的处理以及基于此进行的决策将直接影响物理世界，物联网中数据的真实性显得尤为重要。
大数据是物联网中必须的关键技术，二者的结合能够为物联网系统和应用的发展带来更好的技术基础。以智能安防应用为例，智能安防行业是典型的大数据与物联网相结合的应用场景，物联网技术的普及应用使安防从过去简单的安全防护系统向城市综合化体系演变，涵盖众多的领域，特别是针对重要场所，如机场、银行、地铁、车站、水电气厂、道路桥梁等场所，引入物联网技术后可以通过无线移动、跟踪定位等手段建立全方位的立体防护。智能安防行业需求已从大面积监控布点转变为注重视频智能预警、分析和实战，迫切需要利用大数据技术从海量的视频数据中进行规律预测、情境分析、串并侦查、时空分析等。
基于物联网标识技术，对设备和数据进行统一标识和管理(智能安防领域如监控信号、图像、视频等)，从设备层面解决数据稀疏性问题，从而为大数据的分析和处理奠定底层基础。
采用分类处理技术，基于处理需求对数据进行分类，对实时数据进行流处理，对离线数据进行批处理，从而在保证处理效率的同时提高数据分析的有效性。
物联网与大数据都是当前业界关注的热门技术，如何使二者有机融合在一起，为应用提供网络、数据两方面的基础服务，是物联网和大数据相关应用发展的关键所在。
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