Expand all
') $(accordionID + '-controls .daccord-expandcollapse li').eq(1).hide(); $(accordionID + '-controls .daccord-expandcollapse li').on('click',function () { if ( $(this).index() == 0) { //expand $(accordionID + '-controls .daccord-expandcollapse li').eq(0).hide(); $(accordionID + '-controls .daccord-expandcollapse li').eq(1).show(); $(accordionID + ' .daccord-collapse').slideDown(daccordSpeed); $(accordionID +' .daccord-header').addClass('daccord-header-icon'); } if ( $(this).index() == 1) { //collapse $(accordionID + '-controls .daccord-expandcollapse li').eq(1).hide(); $(accordionID + '-controls .daccord-expandcollapse li').eq(0).show(); $(accordionID + ' .daccord-collapse').slideUp(daccordSpeed); $(accordionID +' .daccord-header').removeClass('daccord-header-icon'); } }); } //if a valid var from url exists override open item setting. var daccordUrlVar = $.getUrlVar('lawenforcement'); if ($.fn.daccordIsInt(daccordUrlVar)) { var urlInt = parseInt(daccordUrlVar); daccordUrlVar = urlInt; properties.openItem = daccordUrlVar; } //Build item object from AEM Vars var daccordItems = []; //Item 1 daccordItems[0] = { itemTitle: "1. Distributed sensing and virtual patrols", itemText: "
Combining emerging technologies to gain greater awareness, faster
Every investigative journey begins with collecting facts about the world. Traditionally, this work has been tough. It could mean relying on a officer's memory of a license plate to look out for, or long hours searching for the right pieces of information. It often means being there, to see, to hear, and to deter—and no department can be everywhere. However, new technologies, like the Internet of Things (IoT) and smart sensors, can be there when needed.
Smart sensors can be used to compile many different types of information to help officers do their jobs faster and more effectively.2 New capabilities can log locations, listen for gunshots, stream video, flag license plates, scan databases, and go on virtual patrol, allowing officers unprecedented awareness in their environments.
These capabilities can provide the raw data which more detailed analytics can use to likely enhance efficiencies and expedite investigations. Most importantly, these technologies can help officers be in the right place, at the right time.
", itemImage: "${item-1-image}", itemImageRight: "${item-1-image-right}", itemMoreText: "${item-1-read-more-text}", itemMoreURL: "${item-1-read-more-url}", itemVideoURL: "${item-1-video-url}", itemInfographicUrl: "${item-1-infographic-url}" }; //Item 2 daccordItems[1] = { itemOpen: "${item-2-open}", itemTitle: "2. Technology as partner in the field", itemText: "
Harnessing digital technologies to improve officer and citizen safety
IoT and distributed sensing are about leveraging new technology to gather information about the world, and point in the right direction. But what should officers do on the scene? New technologies and practices are developing that can help guide action in the world. Advances in areas such as 5G communication, electronics miniaturization, and augmented reality allow people to see, hear, and act in ways that were previously impossible.3
For example, an officer arriving at an unfamiliar situation can now use augmented reality glasses to see pertinent information about prior calls for service from this address, find exits from a building, or see the recent crime history on the block.4 With this information an officer could take precautions to protect themselves and even better serve the public.
If an officer first walking up to a house saw that the occupant has a history of medical conditions, she could immediately bring an Automated External Defibrillator saving time and possibly a life. New technology can also provide digital back up in the field. Small autonomous drones, for example, can be programmed to follow officers, scout locations, and provide video streams so that no officer ever has to go into any situation truly alone.
", itemImage: "${item-2-image}", itemImageRight: "${item-2-image-right}", itemMoreText: "${item-2-read-more-text}", itemMoreURL: "${item-2-read-more-url}", itemVideoURL: "${item-2-video-url}", itemInfographicUrl: "${item-2-infographic-url}" } //Item 3 daccordItems[2] = { itemOpen: "${item-3-open}", itemTitle: "3. Artificial intelligence and predictive policing", itemText: "
Leveraging mountains of data to prevent crime
We live in a world awash in data. And as many departments deploy technology solutions like augmented reality, body cameras, license plate readers, and smart sensors, they will likely generate more data each day than in their entire analog histories.5 The success of future law enforcement strategies rests on being able to quickly and efficiently harness these immense volumes of data to support investigations and enforcement actions. But these mountains of data are too vast for any human to comb through, even if they dedicated an entire lifetime to searching.
To gain real insight, artificial intelligence (AI) and machine learning will be key to future investigations.6 For example, each year more than eight million tips on the location of missing children must be analyzed by a team of just 25 investigators.7 AI is being deployed to help those investigators sift through the data and find the most likely leads to identify exploited children and reunite them with loved ones. AI is already demonstrating its value around the world by helping police in England analyze CCTV video, officers in India find 3,000 missing persons in just four days, and the Dutch to find promising leads in cold cases. 8
By analyzing patterns, sensor feeds, and databases of records, AI could help law enforcement identify critical places to be, find key linkages between suspects, and explore other insights hidden in a sea of data. However, with civil liberties group already calling for bans on technologies such as predictive policing and facial recognition, law enforcement needs to find uses of AI that are effective but also consistent with community expectations. 9
", itemImage: "${item-3-image}", itemImageRight: "${item-3-image-right}", itemMoreText: "${item-3-read-more-text}", itemMoreURL: "${item-3-read-more-url}", itemVideoURL: "${item-3-video-url}", itemInfographicUrl: "${item-3-infographic-url}" }; //Item 4 daccordItems[3] = { itemOpen: "${item-4-open}", itemTitle: "4. Evidence-based policing", itemText: "
Rigorously testing what works and scaling key insights
AI and machine learning can help find the clues to target a patrol or forward an investigation, using simple rule sets to test new hypotheses, identify what works, and scale successes. A similar approach—evidence-based policing—can also be applied to the methods of police work itself. Evidence-based policing includes using advanced forensic techniques to extract more information from the same amount of evidence, but it also goes beyond this to examine the heart of police activities.
Evidence-based policing can analyze data about the outcomes of police interactions to help find the most effective methods and tools while minimizing the use of tactics that tend to make situations worse.10 In an era when many police officers are being asked to do more and more with fewer and fewer resources, evidence-based policing seeks to pair them with outside assistance, such as academic researchers or computer programmers, to help focus their efforts on the most effective police work. That is exactly what the national police of New Zealand found when they established their Evidence Based Policing Centre.
Researchers are now able to comb through data and identify where enforcement actions could be most effective (for example, targeting drug distribution at the island nation's airports) and when officers' time could be better spent elsewhere (using traditional Māori-led decision making mechanisms to improve outcomes for young Māori).11 Using these methods, police were able to design more effective strategies to combat the most complex safety issues facing society, from domestic violence to cybercrime, while redirecting other issues to community support structures.
", itemImage: "${item-4-image}", itemImageRight: "${item-4-image-right}", itemMoreText: "${item-4-read-more-text}", itemMoreURL: "${item-4-read-more-url}", itemVideoURL: "${item-4-video-url}", itemInfographicUrl: "${item-4-infographic-url}" }; //Item 5 daccordItems[4] = { itemOpen: "${item-5-open}", itemTitle: "5. New modes of community involvement", itemText: "
Forging stronger local networks to improve public safety
The mission of law enforcement is the safety of the community, and a strong relationship with the community is critical to the success of every law enforcement organization. Building close ties within the community is about traditional police outreach and local involvement, but it's also about leveraging tools to help people communicate their needs and their risks directly. New technologies can help police develop their ties to the community, by enabling officers to be more aware of and responsive to the needs of their constituents.12
For example, many communities are now using apps where citizens can report minor issues such as graffiti or suspicious activity to police, giving police real time awareness, dynamic prioritization of calls, and the freedom to focus on the most pressing challenges.13 But human relationships cannot be managed by technology alone. Combining innovative approaches such as evidence-based policing can help to re-baseline these relationships by changing the ways and times officers interact with the populace.
Departments can create more opportunities for positive interactions, while working to leverage the expertise, resources, and local knowledge of key stakeholders in the community. Using both technology and training, departments could make it easier for constituents to support public safety, helping to make community-law enforcement relationships healthier and more productive.
", itemImage: "${item-5-image}", itemImageRight: "${item-5-image-right}", itemMoreText: "${item-5-read-more-text}", itemMoreURL: "${item-5-read-more-url}", itemVideoURL: "${item-5-video-url}", itemInfographicUrl: "${item-5-infographic-url}" }; //Item 6 daccordItems[5] = { itemOpen: "${item-6-open}", itemTitle: "${item-6-title}", itemText: "${item-6-text}", itemImage: "${item-6-image}", itemImageRight: "${item-6-image-right}", itemMoreText: "${item-6-read-more-text}", itemMoreURL: "${item-6-read-more-url}", itemVideoURL: "${item-6-video-url}", itemInfographicUrl: "${item-6-infographic-url}" }; //Item 7 daccordItems[6] = { itemOpen: "${item-7-open}", itemTitle: "${item-7-title}", itemText: "${item-7-text}", itemImage: "${item-7-image}", itemImageRight: "${item-7-image-right}", itemMoreText: "${item-7-read-more-text}", itemMoreURL: "${item-7-read-more-url}", itemVideoURL: "${item-7-video-url}", itemInfographicUrl: "${item-7-infographic-url}" }; //Item 8 daccordItems[7] = { itemOpen: "${item-8-open}", itemTitle: "${item-8-title}", itemText: "${item-8-text}", itemImage: "${item-8-image}", itemImageRight: "${item-8-image-right}", itemMoreText: "${item-8-read-more-text}", itemMoreURL: "${item-8-read-more-url}", itemVideoURL: "${item-8-video-url}", itemInfographicUrl: "${item-8-infographic-url}" }; //Item 9 daccordItems[8] = { itemOpen: "${item-9-open}", itemTitle: "${item-9-title}", itemText: "${item-9-text}", itemImage: "${item-9-image}", itemImageRight: "${item-9-image-right}", itemMoreText: "${item-9-read-more-text}", itemMoreURL: "${item-9-read-more-url}", itemVideoURL: "${item-9-video-url}", itemInfographicUrl: "${item-9-infographic-url}" }; //Item 10 daccordItems[9] = { itemOpen: "${item-10-open}", itemTitle: "${item-10-title}", itemText: "${item-10-text}", itemImage: "${item-10-image}", itemImageRight: "${item-10-image-right}", itemMoreText: "${item-10-read-more-text}", itemMoreURL: "${item-10-read-more-url}", itemVideoURL: "${item-10-video-url}", itemInfographicUrl: "${item-10-infographic-url}" }; daccordItems = $.fn.daccordScrubData(daccordItems,properties); //render html within fragID for (i = 0; i = 0)) { $(accordionID + ' #' + properties.fragId + 'collapse' + daccordItems[i].itemNum + 'vid').player({ video: daccordItems[i].itemVideoURL, playerVars: { controls: 2, modestbranding: 0, rel: 0, color: 'white', showinfo: 0, theme: 'dark', autoplay: 0 }, events: { end: daccordVidEnd, play: daccordVidStart, pause: daccordVidStop } }); //show container ({{fragId}}collapse{{itemNum}}vid-cont) $(accordionID + ' #' + properties.fragId + 'collapse' + daccordItems[i].itemNum + 'vid-cont').show(); //hide fallback ({{fragId}}collapse{{itemNum}}vid-fallback) $(accordionID + ' #' + properties.fragId + 'collapse' + daccordItems[i].itemNum + 'vid-fallback').hide(); } } } //set open states if (properties.openItem > -1) { daccordSelected = (properties.openItem - 1); //set item index (minus 1) $(accordionID +' .daccord-collapse').eq(daccordSelected).slideToggle( daccordSpeed ); if (!properties.expandCollapseAll) { $(accordionID +' .daccord-header').eq(daccordSelected).toggleClass('daccord-header-open'); } else { $(accordionID +' .daccord-header').eq(daccordSelected).toggleClass('daccord-header-icon'); } } //set css options within fragID var css = accordionID + ' .daccord-header a {background-color: ' + properties.titlebarBackgroundColor + ' }'; css += accordionID + ' .daccord-header a {color: ' + properties.titlebarFontColor + ' }'; css += accordionID + ' .daccord-header-icon a { background-color: ' + properties.titlebarActiveBackgroundColor + ' }'; css += accordionID + ' .daccord-header-open a { background-color: ' + properties.titlebarActiveBackgroundColor + ' }'; css += accordionID + ' .daccord-header .daccord-header-bar-icon:after { color: ' + properties.titlebarBackgroundColor + ' }'; css += accordionID + ' .daccord-header-icon .daccord-header-bar-icon:after { color: ' + properties.titlebarActiveBackgroundColor + ' }'; css += accordionID + ' .daccord-header-open .daccord-header-bar-icon:after { color: ' + properties.titlebarActiveBackgroundColor + ' }'; $('head').append('
'); //set click events //accordions $(accordionID + ' .daccord-header').on('click',function() { var index = $(this).parent().prevAll().length; //stop (pause) all vids var daccordVidPlayers = $(accordionID + ' iframe.daccord-video'); $.each(daccordVidPlayers, function () { var daccordStopVid = YT.get($(this).attr('id')); daccordStopVid.pauseVideo(); }); if (!properties.expandCollapseAll) { //close open if (daccordSelected > -1) { $(accordionID + ' .daccord-collapse').eq(daccordSelected).slideUp(daccordSpeed); $(accordionID +' .daccord-header').eq(daccordSelected).removeClass('daccord-header-open'); $(accordionID +' .daccord-header').eq(daccordSelected).removeClass('daccord-header-icon'); } if (daccordSelected != index ) { //open selection - add selected state; daccordSelected = index; $(accordionID +' .daccord-collapse').eq(daccordSelected).slideDown(daccordSpeed); $(accordionID +' .daccord-header').eq(daccordSelected).addClass('daccord-header-open'); $(accordionID +' .daccord-header').eq(daccordSelected).addClass('daccord-header-icon'); } else { daccordSelected = -1; } } else { //set selected if collapse all daccordSelected = index; $(accordionID +' .daccord-collapse').eq(index).slideToggle( daccordSpeed ); $(accordionID +' .daccord-header').eq(index).toggleClass('daccord-header-icon'); //check number of items open/closed and set ui //daccord-header-icon var daccordOpenItems = $(accordionID +' .daccord-header-icon').length; //expand if 0 if (daccordOpenItems == 0) { $(accordionID + '-controls .daccord-expandcollapse li').eq(0).show(); $(accordionID + '-controls .daccord-expandcollapse li').eq(1).hide(); } //collapse if all opens if (daccordOpenItems == properties.numberOfItems) { $(accordionID + '-controls .daccord-expandcollapse li').eq(1).show(); $(accordionID + '-controls .daccord-expandcollapse li').eq(0).hide(); } } }); //CTA analytics var elementClicked = false; $('#daccord-' + 'lawenforcement' + " a.daccord-header-bar").click(function(e) { try { var FragType = "FRG-048"; var FragID = "lawenforcement"; var ActionType = "click"; var ctaText = e.currentTarget.textContent.replace(/\s+/g, '-'); s.linkTrackVars = "prop1,prop2,prop3,prop4,prop5,eVar72"; s.eVar72 = PubID+FragType+":"+ActionType+":"+ctaText+":"+FragID; s.eVar72 = s.eVar72.toLowerCase(); s.prop1 = sc_country; s.prop2 = sc_language; s.prop3 = sc_country + ";" + sc_language; if(elementClicked != true) { s.linkTrackEvents = "event71,event72,event23"; s.events = "event71,event72,event23"; elementClicked = true; } else { s.linkTrackEvents = "event71,event23"; s.events = "event71,event23"; } s.tl(this, "o", s.eVar72); } catch(error) { console.error(error); console.log('analytics suite unavailable?'); } }); // hide html frag title/description var hideFragTitleDesc = "${hide-title-description}"; if (hideFragTitleDesc == "title") { $(accordionID).closest(".htmlfragment").find("h3.secondary-headline").remove(); } else if (hideFragTitleDesc == "description") { $(accordionID).closest(".htmlfragment").find("h3.secondary-headline").siblings("p").remove(); } else if (hideFragTitleDesc == "yes" || hideFragTitleDesc == "true" || hideFragTitleDesc == "both") { $(accordionID).closest(".htmlfragment").find("h3.secondary-headline").siblings("p").remove(); $(accordionID).closest(".htmlfragment").find("h3.secondary-headline").remove(); } // add top padding back for topic pages var templateType = dataLayer.page.attributes.pageTemplate; if (templateType == "Deloitte_Full_Topic_Page") { $(accordionID).closest(".standard-white-component").css("padding-top","20px"); } }; daccord(); });