未来的汽车是移动智能终端—智能汽车。移动互联的发展—车联网。汽车安全与无人驾驶—自动化。动力系统的革命—电动汽车。因能源危机和环保压力电动车而得到快速发展。

物联网技术自提出以来迅速引起了业界重视，与物联网相关的专利申请数量迅速增加。本文从对物联网专利进行分析的角度，通过分析各项统计数据，从一个侧面反映出物联网技术发展的现状，有利于国内物联网领域的研发企业提前预测、找出差距、自主选择合适的研究方向。

中国目前属于由工业经济向信息经济迈进的阶段，传统的工业部门开始与互联网产业出现碰撞，这其中既有融合又有颠覆。互联网对之所以对中国经济带来巨大冲击取决于三个方面的因素。策略研究的目的在与寻找实体经济与虚拟经济相互映射的逻辑关系。从策略的角度理解互联网对传统产业的冲击需要找到互联网和传统产业之间的连接器。互联网对传统产业的冲击集中在供应链环节，而传统产业对互联网的诉求在于解决大宗商品流通中环节中效率偏低的问题。

通信设备—今年以来，通信设备行业销售产值增速始终保持在25%左右，高出去年同期平均水平8-10个百分点，成为电子信息制造行业增长的主要力量。移动互联—1-9月，全国3G移动电话用户累计净增13479.4万户，三季度净增4872.8万户，创历史新高。去电信化—2013年以来各基础电信企业“去电信化”经营策略加速实施。4G试验—中国移动透露，关于中国移动进行TD-LTE扩大规模试验已经获得了工信部批复。

中国信息产业网2月14日报道，工信部以破解互联网互联互通难题、强化网络运行安全为重点，以社会关注的热点问题为导向，着力开展网络“畅通工程”，强化顶层设计，着力构建长效机制，在互联互通、电信设施保护、电信网络运行及安全生产、国际通信四方面都取得了较好的成绩。

我们在本篇报告中试图分析智能家居未来的商业模式。我们认为制造向服务转型不可避免，产品+App、信息服务和生活服务将成为未来智能家居主要的三种商业形态。商业模式之一：产品+App。商业模式之二：以黑电为中心的信息服务。商业模式之三：以多元化生活电器为基础的生活服务。智能家居主题将贯穿全年，维持行业评级“增持”。

Baggage handling systems play a vital role in airport operations; they help in improving the overall efficiency of the terminal building located in the airport. The three main functions of BHSs : Moving the luggage from the check-in area to the departure gate of the airport Helping transit passengers move their baggage from one gate to another Moving luggage from the arrival gate of the airport to the luggage claim area, from where the passengers collect their baggage before exit.

Lane departure warning system is an ADAS integrated in a vehicle to assist the driver. It provides improved vehicle safety with a human-machine interface that prevents accidents by focusing on the major causes of collisions. This system works with the help of an integrated camera system that monitors road marking and determines whether the vehicle is running within the lane. The system is highly efficient in warning a driver whenever required and provides improved comfort and driver feedback.

This chapter introduced an energy-minimizing task scheduling strategy in distributed systems. The problem was formulated as an extension of the generalized assignment problem. Seven heuristics were proposed to solve this problem. All seven of these heuristics were greedy heuristics, namely, ObFun, Greedy-Min, Greedy-Deadline, Greedy-Max, MaxMin, MinMin StdDev, and MinMax Std-Dev. The seven heuristics were compared against each other with both small and large problem sizes. The simulation results showed that for small-sized problems, Greedy-Min, Greedy-Deadline, Greedy-Max, MinMin StdDev, and MinMax StdDev performed the best. For large-sized problems, ObFun had superior performance in terms of mean energy consumption and mean makespan against all of the other proposed heuristics.

In this chapter, we have motivated the development of energy-aware job placement in clusters, grids, and clouds. After describing current computing infrastructures, state-of-the-art techniques for making these infrastructures energy efficient, and current resource management approaches, we have identified the challenges underlying the energy-aware job placement problem. We have reviewed relevant works in the literature that attempt to tackle some of these challenges, and detailed one particular approach. Finally, we have discussed remaining limits and outstanding opportunities. Beyond the need to address remaining scientific and technical challenges, we have demonstrated that there are today strong incentives for energy-aware job placement algorithms to be integrated in production systems.

本刊以七大战略性新兴产业——节能环保、新一代信息技术、生物、高端装备制造、新能源、新材料、新能源汽车为研究重点，关注国家高层和各部委的动态，剖析国家和地方的新兴产业政策。本刊设有政策导读、领导讲话、七大战略性新兴产业本周国内外行业动态和重点企业新闻、投资专题四大板块，能够实时监测新兴产业和重点企业动态，把握新兴产业发展方向，研究发展重点，寻求发展机遇。